Kevin Wells

Dr Kevin Wells


Reader in Medical Imaging
+44 (0)1483 686036
30 BA 00

Biography

Biography

Kevin Wells attended university at Kingston and Brunel, before working for almost 5 years as Postdoctoral Fellow in the Radioisotope Imaging group in the Joint Dept of Physics, Institute of Cancer Research/Royal Marsden Hospital. He then worked as Senior Research Fellow in the area of biomedical optics at UCL before taking up an academic position at the University of Bath in 1996. He then moved to Surrey, initially as Lecturer in Medical Imaging, then Senior Lecturer (2008) and Reader from 2014.

He is also the Course Director for the MSc in Medical Imaging.

My publications

Publications

Alnowam MR, Lewis E, Wells K, Guy M (2010) Respiratory motion modelling and prediction using probability density estimation, IEEE Nuclear Science Symposium Conference Record (NSS/MIC) pp. 2465-2469
One of the current major challenges in clinical imaging is modeling and prediction of respiratory motion, for example, in nuclear medicine or external-beam radio therapy. This paper presents preliminary work in developing a method for modeling and predicting the temporal behavior of the anterior surface position during respiration. This is achieved by tracking the anterior surface during respiration and projecting the captured motion sequence data into a lower dimensional space using Principle Component Analysis and extracting the variation in the Abdominal surface and Thoracic surface separately. Modeling is based on learning the multivariate probability distribution of the motion sequence using a joint Probability Distribution Function (PDF) between the variation of the Thoracic surface and Abdomen surface in the Eigen space. Moreover, the prediction model encodes the amplitude of the variation in the Eigen space for both Thoracic surface and Abdominal surface and the derivative of the variation which reflects the motion path (velocity). The joint Probability Distribution Function (PDF) of the prediction model covers the likelihood of each position/phase configuration and the associated maximum-likelihood motion path. Moreover, feeding the real-time tracking data into the model during nuclear medicine acquisition or external-beam radio therapy will facilitate adjusting the model for any changes and overcome irregularities in the observed respiration cycle.
Ashrani AA, Wells K, Lewis E, Guy M, Goswami B (2011) An iterative particle filter approach for respiratory motion estimation in nuclear medicine imaging, Progress in Biomedical Optics and Imaging - Proceedings of SPIE 7962
The continual improvement in spatial resolution of Nuclear Medicine (NM) scanners has made accurate compensation of patient motion increasingly important. A major source of corrupting motion in NM acquisition is due to respiration. Therefore a particle filter (PF) approach has been proposed as a powerful method for motion correction in NM. The probabilistic view of the system in the PF is seen as an advantage that considers the complexity and uncertainties in estimating respiratory motion. Previous tests using XCAT has shown the possibility of estimating unseen organ configuration using training data that only consist of a single respiratory cycle. This paper augments application specific adaptation methods that have been implemented for better PF estimates with an iterative model update step. Results show that errors are further reduced to an extent up to a small number of iterations and such improvements will be advantageous for the PF to cope with more realistic and complex applications. © 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
Abd Rahni AA, Lewis E, Guy MJ, Goswami B, Wells K (2011) A particle filter approach to respiratory motion estimation in nuclear medicine imaging, IEEE Transactions on Nuclear Science 58 (5 PART 1) pp. 2276-2285
With the continual improvement in spatial resolution of Nuclear Medicine (NM) scanners, it has become increasingly important to accurately compensate for patient motion during image acquisition. Respiratory motion produced by normal lung ventilation is a major source of artefacts in NM emission imaging that can affect large parts of the abdominal thoracic cavity. As such, a particle filter (PF) is proposed as a powerful method for motion correction in emission imaging which can successfully account for previously unseen motion. This paper explores a basic PF approach and demonstrates that it is possible to estimate temporally non-stationary motion using training data consisting of only a single respiratory cycle. Evaluation using the XCAT phantom suggests that the PF is a highly promising approach, and can appropriately handle the complex data that arises in clinical situations.
Alnafea MA, Wells K, Guy M, Spyrou NM (2007) Near field corrections for coded aperture imaging in scintimammography, IEEE Nuclear Science Symposium Conference Record 5 pp. 2948-2953
In this work we study the form of artifacts arising with near-field imaging geometries associated with using coded apertures for Scintimammography (SM) using a combination of Monte Carlo Simulation (MCS), Pseudo-Ray Tracing (PRT) and a new, but simple approach called binary mask shift. The latter method predicted the shape artifacts that are due to off-axis sources and finite size of the object but ignores the effect of varying the angle of incidence of the gamma-rays. The background artifact pattern produced by uniform 2D and 3D source objects of different sizes using a PRT method compared with the corresponding data obtained with MCS suggest that both methods produce striking similarities. From these results we are encouraged to believe that the so-called near field distortion observed with distributed planar and 3D sources, as might be found in SM using coded apertures, can be easily predicted and corrected. © 2006 IEEE.
Bradley DA, Wells K (2014) Reprint of: Biomedical applications reviewed: Hot topic areas, Radiation Physics and Chemistry 95 pp. 191-201
Making reference to the British Journal of Radiology and competitor journal titles, we look at the general area of biomedical physics, reviewing some of the associated topics in ionising radiation research attracting interest over the past 2 years. We also reflect on early developments that have paved the way for these endeavours. The talk is illustrated by referring to a number of biomedical physics areas in which this group has been directly involved, including novel imaging techniques that address compositional and structural makeup as well as use of elastically scattered X-ray phase contrast, radiation damage linking to possible pericardial effects in radiotherapy, simulation of microvascularity and oxygenation with a focus of radiation resistant hypoxic tumours, issues of high spatial resolution dosimetry and tissue interface radiotherapy with doses enhanced through use of high atomic number photoelectron conversion media. © 2013 Elsevier Ltd.
Hope C, Sterr A, Elangovan P, Geades N, Windridge D, Wells K, Young K (2013) High throughput screening for mammography using a human-computer interface with Rapid Serial Visual Presentation (RSVP), Proceedings of SPIE - Medical Imaging 8673
The steady rise of the breast cancer screening population, coupled with data expansion produced by new digital screening technologies (tomosynthesis/CT) motivates the development of new, more efficient image screening processes. Rapid Serial Visual Presentation (RSVP) is a new fast-content recognition approach which uses electroencephalography to record brain activity elicited by fast bursts of image data. These brain responses are then subjected to machine classification methods to reveal the expert's 'reflex' response to classify images according to their presence or absence of particular targets. The benefit of this method is that images can be presented at high temporal rates (
Rodriguez Gutierrez D, Wells K, Diaz O, Moran Santana A, Mendichovszky IA, Gordon I (2010) Partial volume effects in dynamic contrast magnetic resonance renal studies, European Journal of Radiology 75 (2) pp. 221-229
This is the first study of partial volume effect in quantifying renal function on dynamic contrast enhanced magnetic resonance imaging. Dynamic image data were acquired for a cohort of 10 healthy volunteers. Following respiratory motion correction, each voxel location was assigned a mixing vector representing the ?overspilling? contributions of each tissue due to the convolution action of the imaging system's point spread function. This was used to recover the true intensities associated with each constituent tissue. Thus, non-renal contributions from liver, spleen and other surrounding tissues could be eliminated from the observed time?intensity curves derived from a typical renal cortical region of interest. This analysis produced a change in the early slope of the renal curve, which subsequently resulted in an enhanced glomerular filtration rate estimate. This effect was consistently observed in a Rutland?Patlak analysis of the time?intensity data: the volunteer cohort produced a partial volume effect corrected mean enhancement of 36% in relative glomerular filtration rate with a mean improvement of 7% in r2 fitting of the Rutland?Patlak model compared to the same analysis undertaken without partial volume effect correction. This analysis strongly supports the notion that dynamic contrast enhanced magnetic resonance imaging of kidneys is substantially affected by the partial volume effect, and that this is a significant obfuscating factor in subsequent glomerular filtration rate estimation.
Alnowam MR, Lewis E, Wells K, Guy M (2010) Marker-less tracking for respiratory motion correction in nuclear medicine, IEEE Nuclear Science Symposium Conference Record (NSS/MIC) pp. 3118-3121 IEEE
This paper present preliminary work in developing a method of using a marker-less tracking system to analyze the natural temporal variations in chest wall configuration during breathing, thus avoiding reliance on a limited number of fiducial markers. This involves using a marker-less video capture of the motion of the abdominal-chest surface and the development of a B-spline model to parameterize this motion. The advantage of the marker-less system that is non-invasive and non-ionizing, thus facilitating high throughput without the need for marker-based patient set-up time.
Bohndiek SE, Blue A, Cabello J, Clark AT, Guerrini N, Evans PM, Harris EJ, Konstantinidis A, Maneuski D, Osmond J, O'Shea V, Speller RD, Turchetta R, Wells K, Zin H, Allinson NM (2009) Characterization and testing of LAS: A prototype 'large area sensor' with performance characteristics suitable for medical imaging applications, IEEE Transactions on Nuclear Science 56 (5) pp. 2938-2946
The Large Area Sensor (LAS) is a 1350 × 1350 array of active pixels on a 40m pitch fabricated in a 0.35m CMOS process. Stitching technology is employed to achieve an area of 5.4 cm × 5.4 cm. The sensor includes 'regions of reset', whereby three different integration times can be set on the array to achieve a large imaging range for static scenes. Characterization of the noise performance included temporal and fixed pattern sources. LAS was found to have a read noise of 62 e-, a full well capacity of 61 × 10 3 e- and a conversion gain of 5 e- per digital number (DN). The fixed pattern noise (FPN) was evaluated at half saturation; within a single stitched section of the array, column-to-column FPN was found to be 0.6%, while the pixel-to-pixel FPN was 3%. Both FPN sources were found to be gain related and could be corrected via flat fielding. Based on the results of characterization, LAS was coupled to a structured CsI:Tl scintillator and included in an X-ray diffraction system developed for the analysis of breast biopsy samples. Data acquired with plastic test objects agrees with that acquired by a previous prototype sensor. It is demonstrated that an imaging output range of 140 dB can be achieved using integration times of 0.1 ms to record the transmitted X-ray beam and 2.3 s to record the lower intensity scattered radiation. © 2009 IEEE.
Yip M, Zanca F, MacKenzie A, Workman A, Young KC, Dance DR, Bosmans H, Lewis E, Wells K (2010) Validation of a simulated dose reduction methodology using digital mammography CDMAM images and mastectomy images, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6136 LNCS pp. 78-85
The purpose of this study is to evaluate the effect of simulated dose reduction using CDMAM and mastectomy images acquired on two digital mammography systems. High dose images have been artificially degraded to reduced dose levels by systematically adding filtered noise. Automated scoring has been carried out on the degraded CDMAM images and on experimental CDMAM images, taken at the same corresponding reduced doses. Contrast-detail curves were derived for both, at all doses, and compared. Relative difference in the contrast-detail curves was approximately 5% overall for all four doses. For the mastectomy images noise power spectra were obtained and the ratio of experimental to synthetic low dose NPS profiles averaged for all doses at 1.04. The largest differences in the NPS profiles were found at the high spatial frequencies, corresponding with the differences in the small discs in the contrast-detail curves. © 2010 Springer-Verlag.
Zoglopitou L, Wells K, Holubinka M, Mahmood S (2012) Study of the Optimisation of the CT Transmission Parameters for the Attenuation Correction of PET Data, EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING 39 pp. S368-S368 SPRINGER
Rahni AAA, Lewis E, Wells K (2014) Quantication and analysis of respiratory motion from 4D MRI, Journal of Physics: Conference Series 546 (1)
© Published under licence by IOP Publishing Ltd.It is well known that respiratory motion affects image acquisition and also external beam radiotherapy (EBRT) treatment planning and delivery. However often the existing approaches for respiratory motion management are based on a generic view of respiratory motion such as the general movement of organ, tissue or fiducials. This paper thus aims to present a more in depth analysis of respiratory motion based on 4D MRI for further integration into motion correction in image acquisition or image based EBRT. Internal and external motion was first analysed separately, on a per-organ basis for internal motion. Principal component analysis (PCA) was then performed on the internal and external motion vectors separately and the relationship between the two PCA spaces was analysed. The motion extracted from 4D MRI on general was found to be consistent with what has been reported in literature.
Konstantinidis AC, Zheng Y, Olivo A, Bliznakova K, Yip M, Anaxagoras T, Wells K, Allinson N, Speller RD (2012) Evaluation of a novel wafer-scale CMOS APS X-ray detector for use in mammography, IEEE Nuclear Science Symposium Conference Record pp. 3254-3260
The most important factors that affect the image quality are contrast, spatial resolution and noise. These factors and their relationship are quantitatively described by the Contrast-to-Noise Ratio (CNR), Signal-to-Noise Ratio (SNR), Modulation Transfer Function (MTF), Noise Power Spectrum (NPS) and Detective Quantum Efficiency (DQE) parameters. The combination of SNR, MTF and NPS determines the DQE, which represents the ability to visualize object details of a certain size and contrast at a given dose. In this study the performance of a novel large area Complementary Metal-Oxide-Semiconductor (CMOS) Active Pixel Sensor (APS) X-ray detector, called DynAMITe (Dynamic range Adjustable for Medical Imaging Technology), was investigated and compared to other three digital mammography systems (namely a) Large Area Sensor (LAS), b) Hamamatsu C9732DK, and c) Anrad SMAM), in terms of physical characteristics and evaluation of the image quality. DynAMITe detector consists of two geometrically superimposed grids: a) 2560 × 2624 pixels at 50 ¼m pitch, named Sub-Pixels (SP camera) and b) 1280 × 1312 pixels at 100 ¼m pitch, named Pixels (P camera). The X-ray performance evaluation of DynAMITe SP detector demonstrated high DQE results (0.58 to 0.64 at 0.5 lp/mm). Image simulation based on the X-ray performance of the detectors was used to predict and compare the mammographic image quality using ideal software phantoms: a) one representing two three dimensional (3-D) breasts of various thickness and glandularity to estimate the CNR between simulated microcalcifications and the background, and b) the CDMAM 3.4 test tool for a contrast-detail analysis of small thickness and low contrast objects. The results show that DynAMITe SP detector results in high CNR and contrast-detail performance. © 2012 IEEE.
Yip M, Saripan MI, Wells K, Bradley DA (2015) Monte Carlo Simulations for the Detection of Buried Objects Using Single Sided Backscattered Radiation, PLOS ONE 10 (9) ARTN e0135769 PUBLIC LIBRARY SCIENCE
Esposito M, Anaxagoras T, Fant A, Wells K, Konstantinidis A, Osmond JPF, Evans PM, Speller RD, Allinson NM (2011) DynAMITe: a Large Area Sensor for Biomedical Applications with Bimodal Dynamic Range and Resolution,
In many biomedical imaging applications there is a strong demand for large area sensors. Nowadays the most common detectors in this field are Flat Panel imagers which offer a reasonably large area, typically greater than 20 cm×20 cm. Even so such detectors present severe drawbacks such as large pixels, high noise, low frame rate and excessive image artefacts. In the last two decades Active Pixel Sensors (APSs) have gained popularity because of a potential for overcoming such issues. Furthermore, in recent years, improvements in design and fabrication techniques have made available fabricative processes for wafer scale imagers, which can be now seamlessly scaled from a few centimetres square up to the whole wafer size. A suitable detector for biomedical imaging application needs to fulfil specific requirements: it should have a high spatial resolution, a low noise and a high dynamic range. These figures of merit are connected with the pixel size. Since the pixel size is normally fixed at the time of the design, spatial resolution, noise and dynamic range cannot be further optimized. The authors propose a novel edge-buttable wafer scale APS (12.8 cm×12.8 cm), named the Dynamic range Adjustable for Medical Imaging Technology or DynAMITe, developed by the Multidimensional Integrated Intelligent Imaging Plus (MI-3 Plus) consortium.
This APS is based on the use of two different diode geometries in the same pixel array and with different size active pixels. As the effective pixel size is no longer fixed, but two different pixel sizes are used for the whole detector matrix, this detector can deliver two inherently different
resolutions each with different noise and saturation performance in the same pixel array. The DynAMITe design has great potential for use in a variety of biomedical imaging applications. In its initial deployment the authors will be developing demonstrators in radiotherapy portal imaging, breast mammography and diffraction imaging and also in sequencing methods for the life sciences.
Bradley DA, Wells K (2013) Biomedical applications reviewed: Hot topic areas, Radiation Physics and Chemistry 85 pp. 42-52
Making reference to the British Journal of Radiology and competitor journal titles, we look at the general area of biomedical physics, reviewing some of the associated topics in ionising radiation research attracting interest over the past 2 years. We also reflect on early developments that have paved the way for these endeavours. The talk is illustrated by referring to a number of biomedical physics areas in which this group has been directly involved, including novel imaging techniques that address compositional and structural makeup as well as use of elastically scattered X-ray phase contrast, radiation damage linking to possible pericardial effects in radiotherapy, simulation of microvascularity and oxygenation with a focus of radiation resistant hypoxic tumours, issues of high spatial resolution dosimetry and tissue interface radiotherapy with doses enhanced through use of high atomic number photoelectron conversion media. © 2012 Elsevier Ltd.
Alnafea M, Wells K, Spyrou NM, Saripana MI, Guy M, Hinton P (2006) Preliminary results from a Monte Carlo study of breast tumour imaging with low-energy high-resolution collimator and a modified uniformly-redundant array-coded aperture, NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 563 (1) pp. 146-149 ELSEVIER SCIENCE BV
Smith RL, Abd Rahni A, Jones J, Wells K (2013) Adaptive recursive Bayesian estimation using expectation maximization for respiratory motion correction in Nuclear Medicine, IEEE Nuclear Science Symposium Conference Record
A method to correct for irregular, non stationary respiratory motion is required to improve quantitative and qualitative accuracy of Nuclear Medicine Images. Solutions to date rely on temporally regular respiratory motion with static models learnt from training data. An adaptive approach with dynamic parameter learning of motion models is required. To this avail we cast respiratory motion estimation as a Hidden Markov model. An expectation maximization based Kalman smoother algorithm is utilized to infer hidden states of motion from observations of the patient's chest motion alone. The framework is validated using a computational anthropomorphic phantom (XCAT) with seven respiratory cycles with varying amplitude and frequency. A PET study is simulated with four 16mm lung lesions to assess the effectiveness of the approach. Preliminary tests are also performed on dynamic MRI data of a single volunteer. The likelihood of dynamical model fitting is monitored for individual respiratory cycles. Optimal estimates of previously unseen motion are made using the Kalman smoother. The proposed method can correct for respiratory motion to the order of 1.5mm. A thirty percent increase in mean uptake value for the corrected tumors in the simulated PET study was observed. © 2013 IEEE.
Esposito M, Diaz O, Wells K, Anaxagoras T, Allinson NM (2012) Radiation hardness of a large area CMOS active pixel sensor for bio-medical applications, IEEE Nuclear Science Symposium Conference Record pp. 1300-1304 IEEE
A wafer scale CMOS Active Pixel Sensor has been designed employing design techniques of transistor enclosed geometry and P+ doped guard rings to offer ionizing radiation tolerance. The detector was irradiated with 160 kVp X-rays up to a total dose of 94 kGy(Si) and remained functional. The radiation damage produced in the device has been studied, resulting in a dark current density increase per decade of 96±5 pA/cm/decade and a damage threshold of 204 Gy(Si). The damage produced in the detector has been compared with a commercially available CMOS APS, showing a radiation tolerance about 100 times higher. Moreover Monte Carlo simulations have been performed to evaluate primary and secondary energy deposition in each of the detector stages. © 2012 IEEE.
Cabello J, Wells K, Metaxas A, Bailey A, Kitchen I, Clark A, Prydderch A, Turchetta R (2007) Digital Autoradiography imaging using CMOS technology: First Tritium Autoradiography with a back-thinned CMOS detector and comparison of CMOS imaging performance with autoradiography film, 2007 IEEE NUCLEAR SCIENCE SYMPOSIUM CONFERENCE RECORD, VOLS 1-11 pp. 3743-3746 IEEE
Smith RL, Rahni AA, Jones J, Wells K (2012) Recursive Bayesian estimation for respiratory motion correction in nuclear medicine imaging, IEEE Nuclear Science Symposium Conference Record pp. 2942-2945
Respiratory motion correction degrades quantitatively and qualitatively Nuclear Medicine images. We propose that adaptive approaches are required to correct for the irregular breathing patterns often encountered in the clinical setting, which can be addressed within a Bayesian tracking formulation. This allows inference of the hidden organ configurations using only knowledge of an external observation such as a parametrized external surface. The flexible framework described provides a method to correct for organ motion whilst accommodating for irregular unseen respiratory patterns. In this work we utilize a Kalman filter and compare it with a Particle filter. A novel adaptive state transition model is also introduced to describe the evolution of organ configurations. The Kalman filter marginally outperforms the Particle filter, both approaches however offer an effective motion correction mechanism, correcting for motion with errors of around 1-3mm. We present results of simulated PET images derived from XCAT to demonstrate the efficacy of the approach. © 2012 IEEE.
Esposito M, Anaxagoras T, Fant A, Kostantinidis A, Wells K, Osmond JPF, Evans PM, Speller RD, Allinson NM (2011) DynAMITe: A Wafer Scale Sensor for Biomedical Applications,
Wafer scale detector technology represents an alternative approach for biomedical imaging where currently Flat Panel Imagers (FPIs) are the most common option. However, FPIs possess several key drawbacks such as large pixels, high noise, low frame rates, and excessive image artefacts. Recently Active Pixel Sensors have gained popularity overcoming such issues and are now scalable up to wafer size by appropriate reticule stitching. Detectors for biomedical imaging applications require high spatial resolution, low noise and high dynamic range. These figures of merit are related to pixel size and as the pixel size is fixed at the time of the design, spatial resolution, noise and dynamic range cannot be further optimized. The authors report on a new rad-hard monolithic APS, named DynAMITe (Dynamic range Adjustable for Medical Imaging Technology), developed by the UK MI-3 Plus consortium. This large area detector (12.8 x 12.8 cm2) is based on the use of two different diode geometries within the same pixel array with different size pixels (50 um and100 um). Hence the resulting camera can possess two inherently different resolutions each with different noise and saturation performance. The small pixels and the large pixels can be reset at different voltages, resulting in different depletion widths. The larger depletion width for the small pixels allows the initial generated photo-charge to be collected by the small pixels, which ensures an intrinsically lower noise and higher spatial resolution. After these pixels reach near saturation, the larger pixels start collecting so offering a higher dynamic range whereas the higher noise floor is not important as at higher signal levels performance is set by Poisson noise. Further different reset voltage can selectively choose the operating resolution of the detector leading to a true pixel binning.
Rashidnasab A, Elangovan P, Yip M, Diaz O, Dance DR, Young KC, Wells K (2013) Simulation and assessment of realistic breast lesions using fractal growth models, Physics in Medicine and Biology 58 (16) pp. 5613-5627
A new method of generating realistic three dimensional simulated breast lesions known as diffusion limited aggregation (DLA) is presented, and compared with the random walk (RW) method. Both methods of lesion simulation utilize a physics-based method for inserting these simulated lesions into 2D clinical mammogram images that takes into account the polychromatic x-ray spectrum, local glandularity and scatter. DLA and RW masses were assessed for realism via a receiver operating characteristic (ROC) study with nine observers. The study comprised 150 images of which 50 were real pathology proven mammograms, 50 were normal mammograms with RW inserted masses and 50 were normal mammograms with DLA inserted masses. The average area under the ROC curve for the DLA method was 0.55 (95% confidence interval 0.51-0.59) compared to 0.60 (95% confidence interval 0.56-0.63) for the RW method. The observer study results suggest that the DLA method produced more realistic masses with more variability in shape compared to the RW method. DLA generated lesions can overcome the lack of complexity in structure and shape in many current methods of mass simulation. © 2013 Institute of Physics and Engineering in Medicine.
Tahavoria F, Adams E, Dabbs M, Aldridge L, Liversidge N, Donovan E, Jordan T, Evans PM, Wells K (2015) Combining Marker-less Patient Setup and Respiratory Motion Monitoring Using Low Cost 3D Camera Technology, MEDICAL IMAGING 2015: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING 9415 SPIE-INT SOC OPTICAL ENGINEERING
Abd Rahni AA, Wells K, Lewis E, Guy M, Goswami B (2011) An Iterative Particle Filter Approach for Respiratory Motion Estimation in Nuclear Medicine Imaging, MEDICAL IMAGING 2011: IMAGE PROCESSING 7962 SPIE-INT SOC OPTICAL ENGINEERING
Esposito M, Anaxagoras T, Fant A, Wells K, Konstantinidis A, Osmond JPF, Evans PM, Speller RD, Allinson NM (2011) DynAMITe: A Wafer Scale Sensor for Biomedical Applications, Journal of Instrumentation 6 (C)
In many biomedical imaging applications Flat Panel Imagers (FPIs) are currently the most common option. However, FPIs possess several key drawbacks such as large pixels, high noise, low frame rates, and excessive image artefacts. Recently Active Pixel Sensors (APS) have gained popularity overcoming such issues and are now scalable up to wafer size by appropriate reticule stitching. Detectors for biomedical imaging applications require high spatial resolution, low noise and high dynamic range. These figures of merit are related to pixel size and as the pixel size is fixed at the time of the design, spatial resolution, noise and dynamic range cannot be further optimized. The authors report on a new rad-hard monolithic APS, named DynAMITe (Dynamic range Adjustable for Medical Imaging Technology), developed by the UK MI-3 Plus consortium. This large area detector (12.8 cm × 12.8 cm) is based on the use of two different diode geometries within the same pixel array with different size pixels (50 ¼m and 100 ¼m). Hence the resulting device can possess two inherently different resolutions each with different noise and saturation performance. The small and the large pixel cameras can be reset at different voltages, resulting in different depletion widths. The larger depletion width for the small pixels allows the initial generated photo-charge to be promptly collected, which ensures an intrinsically lower noise and higher spatial resolution. After these pixels reach near saturation, the larger pixels start collecting so offering a higher dynamic range whereas the higher noise floor is not important as at higher signal levels performance is governed by the Poisson noise of the incident radiation beam. The overall architecture and detailed characterization of DynAMITe will be presented in this paper.
Mackenzie A, Workman A, Dance DR, Yip M, Wells K, Young KC (2010) Adapting clinical images to appear with different noise and sharpness to model a different detector, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6136 LNCS pp. 319-326
Comparing the clinical performance of digital mammography technologies is challenging. The aim of this work is to develop and test a methodology for adjusting mammographic images taken on a given imaging system to simulate their appearance as if taken on a different system. Such methodology would be very useful for a wide range of system performance and design studies using both phantom and clinical images. The process involves changing the image blurring in accordance with the measured modulation transfer functions and adding noise (electronic, quantum and structure). The method has been tested by adapting flat field images acquired using an amorphous selenium detector and a computed radiography (CR) detector to different dose levels and comparing the resultant simulated NPSs with directly measured NPSs. For the detectors used in this work the NPSs at different dose levels are well predicted. This could be a powerful tool for studies of clinical image quality. © 2010 Springer-Verlag.
Elangovan P, Dance DR, Young KC, Wells K (2016) Generation of 3D synthetic breast tissue, MEDICAL IMAGING 2016: PHYSICS OF MEDICAL IMAGING 9783 SPIE-INT SOC OPTICAL ENGINEERING
Elangovan P, Warren LM, Mackenzie A, Rashidnasab A, Diaz O, Dance DR, Young KC, Bosmans H, Strudley CJ, Wells K (2014) Development and validation of a modelling framework for simulating 2D-mammography and breast tomosynthesis images, Physics in Medicine and Biology 59 (15) pp. 4275-4293
Planar 2D x-ray mammography is generally accepted as the preferred screening technique used for breast cancer detection. Recently, digital breast tomosynthesis (DBT) has been introduced to overcome some of the inherent limitations of conventional planar imaging, and future technological enhancements are expected to result in the introduction of further innovative modalities. However, it is crucial to understand the impact of any new imaging technology or methodology on cancer detection rates and patient recall. Any such assessment conventionally requires large scale clinical trials demanding significant investment in time and resources. The concept of virtual clinical trials and virtual performance assessment may offer a viable alternative to this approach. However, virtual approaches require a collection of specialized modelling tools which can be used to emulate the image acquisition process and simulate images of a quality indistinguishable from their real clinical counterparts. In this paper, we present two image simulation chains constructed using modelling tools that can be used for the evaluation of 2D-mammography and DBT systems. We validate both approaches by comparing simulated images with real images acquired using the system being simulated. A comparison of the contrast-to-noise ratios and image blurring for real and simulated images of test objects shows good agreement (
Yip M, Chukwu W, Kottis E, Lewis E, Oduko J, Gundogdu O, Young KC, Wells K (2009) Automated scoring method for the CDMAM phantom, Progress in Biomedical Optics and Imaging - Proceedings of SPIE 7263
CDMAM phantoms are widely used in the Europe to assess the performance of mammography systems utilising small size and low contrast disc details. However, the assessment of CDMAM images by human observers is slow and tedious. An automated method for scoring CDMAM images (CDCOM) is widely available to address this issue. We have developed an alternative automated scoring tool to score CDMAM images, Quantitative Assessment System (QAS), for similarly removing inter- and intra- observer variability. This provides additional valuable information about the contrast and SNR of each gold disc within the image. The QAS scores CDMAM phantom images using a scanning algorithm. QAS scoring results were compared with human observers and with CDCOM. It was found that QAS was comparable with human observers in scoring, whereas CDCOM consistently scored a higher number of discs correctly in CDMAM images compared with QAS and human observers. QAS results have been used to analyse the effects of different digital mammography system modulation transfer functions (MTFs) on fine details for a number of systems in the form of contrast degradation factor (CDF) measurements. CDF curves for experimentally acquired CDMAM images were compared with those for simulated CDMAM images to assess the accuracy of contrast measurements.
Wells K, Chiverton J, Partridge M, Barry M, Kadhem H, Ott B (2007) Quantifying the partial volume effect in PET using Benford's law, IEEE TRANSACTIONS ON NUCLEAR SCIENCE 54 (5) pp. 1616-1625 IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Díaz O, Yip M, Cabello J, Dance DR, Young KC, Wells K (2010) Monte Carlo simulation of scatter field for calculation of contrast of discs in synthetic CDMAM images, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6136 LNCS pp. 628-635
This paper reports on a further development of an image simulation chain, and in particular, the inclusion of contrast degradation across an image using scatter to primary ratios calculated using Monte Carlo simulation. The Monte Carlo technique, using the Geant4 toolkit, has been implemented to model the scatter conditions when imaging the CDMAM phantom with commercial digital mammography. Observed differences between linear and cellular anti scatter grid are presented and discussed. These results support previous assumptions taken by Yip et al.[1]. © 2010 Springer-Verlag.
Hadjipanteli A, Elangovan P, Looney PT, Mackenzie A, Wells K, Dance DR, Young KC (2016) Detection of microcalcification clusters by 2D-mammography and narrow and wide angle digital breast tomosynthesis, MEDICAL IMAGING 2016: PHYSICS OF MEDICAL IMAGING 9783 SPIE-INT SOC OPTICAL ENGINEERING
Cabello J, Holland A, Holland K, Bailey A, Kitchen I, Wells K (2009) Betacam: A commercial approach to ²- Autoradiography, Proceedings of SPIE: Poster Session: Detectors 7258
Autoradiography is a well established imaging modality in Biology and Medicine. This aims to measure the location and concentration of labelled molecules within thin tissue sections. The brain is the most anatomically complex organ and identification of neuroanatomical structures is still a challenge particularly when small animals are used for pre-clinical trials. High spatial resolution and high sensitivity are therefore necessary. This work shows the performance and ability of a prototype commercial system, based on a Charged-Couple Device (CCD), to accurately obtain detailed functional information in brain Autoradiography. The sample is placed in contact with the detector enabling direct detection of ²- particles in silicon, and the system is run in a range of quasi-room temperatures (17-22 °C) under stable conditions by using a precision temperature controller. Direct detection of ²- particles with low energy down to ~5 keV from 3[H] is possible using this room temperature approach. The CCD used in this work is an E2V CCD47-20 frame-transfer device which removes the image smear arising in conventional full-frame imaging devices. The temporal stability of the system has been analyzed by exposing a set of 14[C] calibrated microscales for different periods of time, and measuring the stability of the resultant sensitivity and background noise. The thermal performance of the system has also been analyzed in order to demonstrate its capability of working in other life science applications, where higher working temperatures are required. Once the performance of the system was studied, a set of experiments with biological samples, labelled with typical ²- radioisotopes, such as 3[H], has been carried out to demonstrate its application in life sciences.
Kiani S, Windridge D, Wells K, Gordon I (2012) On-line spatio-temporal independent component analysis for motion correction in renal DCE-MRI, IEEE Nuclear Science Symposium Conference Record pp. 2910-2915
Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) renography, in common with other medical imaging techniques, is influenced by respiratory motion. As a result, data quantification may be inaccurate. This work presents a novel on-line approach for motion correction by implementing a spatio-temporal independent component analysis method (STICA). This methodology firstly results in removal of motion artefacts and secondly provides independent components that have physiological characteristics. The STICA was applied to 10 healthy volunteers' renal DCE-MRI data. The results were evaluated using independent component curve gradients (ICGs) from different regions of interest and by comparing them with the Rutland-Patlak (RP) analysis. The r values for the ICGs were significantly higher compared to the RP curves. The standard deviations of the IC curve gradients also showed less dispersion with comparison to the RP curve gradients across all the ten volunteers' renal data. © 2012 IEEE.
Abd Rahni AA, Lewis E, Wells K (2013) Robustness of recursive Bayesian estimation of respiratory motion with inter-cycle variation, IEEE Nuclear Science Symposium Conference Record
Compensation of respiratory motion has been identified as a crucial factor in achieving high resolution Nuclear Medicine (NM) imaging. Many motion correction approaches have been studied and they are seen to have advantages over simpler motion compensation approaches such as respiratory gating. However, all motion correction approaches rely on an assumption or estimation of respiratory motion. This paper builds upon previous work in recursive Bayesian estimation (RBE) of respiratory motion assuming stereo camera observation of external respiratory motion. In this paper, additional stereo-camera derived XCAT cycles are used to evaluate the robustness of RBE with inter-cycle variation. © 2013 IEEE.
Abd Rahni AA, Lewis E, Wells K, Guy M, Goswami B (2010) Development of a Particle Filter Framework for Respiratory Motion Correction in Nuclear Medicine Imaging, MEDICAL IMAGING 2010: IMAGE PROCESSING 7623 SPIE-INT SOC OPTICAL ENGINEERING
Esposito M, Newcombe J, Anaxagoras T, Allinson NM, Wells K (2012) Using a large area CMOS APS for direct chemiluminescence
detection in Western Blotting Electrophoresis,
Proceedings of SPIE 8317
Western blotting electrophoretic sequencing is an analytical technique widely used in Functional Proteomics to detect, recognize and quantify specific labelled proteins in biological samples. A commonly used label for western blotting is Enhanced ChemiLuminescence (ECL) reagents based on fluorescent light emission of Luminol at 425nm. Film emulsion is the conventional detection medium, but is characterized by non-linear response and limited dynamic range. Several western blotting digital imaging systems have being developed, mainly based on the use of cooled Charge Coupled Devices (CCDs) and single avalanche diodes that address these issues. Even so these systems present key drawbacks, such as a low frame rate and require operation at low temperature. Direct optical detection using Complementary Metal Oxide Semiconductor (CMOS) Active Pixel Sensors (APS)could represent a suitable digital alternative for this application. In this paper the authors demonstrate the viability of direct chemiluminescent light detection in western blotting electrophoresis using a CMOS APS at room temperature. Furthermore, in recent years, improvements in fabrication techniques have made available reliable processes for very large imagers, which can be now scaled up to wafer size, allowing direct contact imaging of full size western blotting samples. We propose using a novel wafer scale APS (12.8 cm×13.2 cm), with an array architecture using two different pixel geometries that can deliver an inherently low noise and high dynamic range image at the same time representing a dramatic improvement with respect to the current western blotting imaging systems.
Alnowami MR, Lewis E, Guy M, Wells K (2010) An Observation Model for Motion Correction in Nuclear Medicine, MEDICAL IMAGING 2010: IMAGE PROCESSING 7623 SPIE-INT SOC OPTICAL ENGINEERING
Jones J, Lewis E, Guy M, Wells K (2009) A virtual dissection based registration to model patient-specific respiratory motion, IEEE Nuclear Science Symposium Conference Record pp. 3571-3576
This work is directed at reducing patient induced blurring in SPECT imaging due to breathing motion. As image resolution improves this breathing motion is becoming increasingly significant. Method: The NCAT phantom and an associated medical image processing package (RMDP) are used to obtain a breathing cycle of images (both CT and corresponding SPECT) and a full organ segmentation. A process termed 'virtual dissection' is undertaken which sees individual organs extracted from the main images and independently registered (ICP). These individual registrations are reconciled, combined and used to obtain improved final images. Results: The results of the objective validation techniques are presented together with a comparison of processed and unprocessed images. Conclusion: Within the scope of the synthetic data used and for organs for which the assumption of near-rigid motion holds well the technique works. In the case of the ribs and lungs further development is needed. ©2009 IEEE.
Rahni AAA, Lewis E, Guy MJ, Goswami B, Wells K (2010) Performance evaluation of a particle filter framework for respiratory motion estimation in Nuclear Medicine imaging, IEEE Nuclear Science Symposium Conference Record (NSS/MIC) pp. 2676-2680 IEEE
With the continual improvement in spatial resolution of Nuclear Medicine (NM) scanners, it has become increasingly important to accurately compensate for patient motion during acquisition. Respiratory motion produced by lung ventilation is a major source of artefacts in NM that can affect large parts of the abdominal-thoracic cavity. As such, a particle filter (PF) is proposed as a powerful method for motion correction in NM imaging. This paper explores a basic PF approach and demonstrates that it is possible to estimate non-stationary motion using a single respiratory cycle as training data. Using the XCAT phantom, 7 test datasets that vary in depth and rate of respiration were generated. The results using these datasets show that the PF has an average Euclidean distance error over all voxels of only 1.7 mm, about half of the typical dimensions of an NM voxel for clinical applications. The conclusion is that use of the PF is promising, and can be adapted to handle more sophisticated data such as those that arise in clinical situations.
MacKenzie A, Workman A, Dance DR, Yip M, Wells K, Young KC (2011) Validation of a method to convert an image to appear as if acquired using a different digital detector, Proceedings of SPIE: Poster Session: X-ray Imaging 7961
A method to convert digital mammograms acquired on one system to appear as if acquired using another system is presented. This method could be used to compare the clinical efficacy of different systems. The signal transfer properties modulation transfer function (MTF) and noise power spectra (NPS) were measured for two detectors - a computed radiography (CR) system and a digital radiography (DR) system. The contributions to the NPS from electronic, quantum and structure sources were calculated by fitting a polynomial at each spatial frequency across the NPS at each dose. The conversion process blurs the original image with the ratio of the MTFs in frequency space. Noise with the correct magnitude and spatial frequency was added to account for differences in the detector response and dose. The method was tested on images of a CDMAM test object acquired on the two systems at two dose levels. The highest dose images were converted to lower dose images for the same detector, then images from the DR system were converted to appear as if acquired at a similar dose using CR. Contrast detail curves using simulated CDMAM images closely matched those of real images.
Loveland J, Gundogdu O, Morton E, Wells K, Bradley DA (2010) Phase contrast imaging: Effect of increased objectdetector distances at X-ray diagnostic and megavoltage energies, Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 652 (1) pp. 625-629
The effect of varying object to detector separation at constant and varying magnification has been investigated at an accelerating potential of 30 kVp. Edge-contrast enhancement provided by phase effects was investigated for a drinking straw and found to provide up to 2.52±0.02× the contrast for a PVC Heaviside step function. An optimum magnification of 1.5× was found to apply for the microfocus X-ray tube setup used. Imaging at nominal megavoltage energies was investigated using a Rapiscan Systems Eagle M4500 series scanner. For a fixed sourcedetector separation, increased magnification improved edge contrast and spatial resolution. © 2010 Elsevier B.V.
Bradley DA, Hashim S, Cabello J, Wells K, Dunn WL (2010) Photon-induced positron annihilation for standoff bomb detection, NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 619 (1-3) pp. 415-418 ELSEVIER SCIENCE BV
Bradley DA, Wells K (2013) Biomedical applications reviewed: Hot topic areas, Radiation Physics and Chemistry
Making reference to the British Journal of Radiology and competitor journal titles, we look at the general area of biomedical physics, reviewing some of the associated topics in ionising radiation research attracting interest over the past 2 years. We also reflect on early developments that have paved the way for these endeavours. The talk is illustrated by referring to a number of biomedical physics areas in which this group has been directly involved, including novel imaging techniques that address compositional and structural makeup as well as use of elastically scattered X-ray phase contrast, radiation damage linking to possible pericardial effects in radiotherapy, simulation of microvascularity and oxygenation with a focus of radiation resistant hypoxic tumours, issues of high spatial resolution dosimetry and tissue interface radiotherapy with doses enhanced through use of high atomic number photoelectron conversion media. © 2012 Elsevier Ltd. All rights reserved.
Alnowami M, Lewis E, Wells K (2012) Internal motion prediction using kernel density estimation and general canonical correlation model, IEEE Nuclear Science Symposium Conference Record pp. 3772-3776
This paper presents preliminary work in developing a global correlation model between lung tumor respiratory motion and external surrogate motion in external beam radiotherapy. This involves using a combination of set of dynamic CT datasets to train a bivariate kernel density estimation model. Canonical correlation analysis (CCA) is used to parametrize the correlation between the external observation surrogate and the target region, in this case tumor temporal motion. Such an approach is non-invasive and non-ionizing, and minimizes the patient setup time. Preliminary results shows that the correlation coefficient for preliminary data is high, ranging between 0.87 and 0.99. Recasting the internal and external motion into eigenspace reveals the underlying correlation in an efficient and compact manner. A leave-one-out method was used to validate the proposed algorithm. The average error of tumor position was about 1.6 mm. © 2011 IEEE.
Rashidnasab A, Elangovan P, Dance DR, Young KC, Diaz O, Wells K (2012) Modeling realistic breast lesions using diffusion limited aggregation, Progress in Biomedical Optics and Imaging - Proceedings of SPIE 8313
Synthesizing the appearance of malignant masses and inserting these into digital mammograms can be used as part of a wider framework for investigating the radiological detection task in X-ray mammography. However, the randomness associated with cell division within cancerous masses and the associated complex morphology challenges the realism of the modeling process. In this paper, Diffusion Limited Aggregation (DLA), a type of fractal growth process is proposed and utilized for modeling breast lesions. Masses of different sizes, shapes and densities were grown by controlling DLA growth parameters either prior to growth, or dynamically updating these during growth. A validation study was conducted by presenting 30 real and 30 simulated masses in a random order to a team of radiologists. The results from the validation study suggest that the observers found it difficult to differentiate between the real and simulated lesions. © 2012 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
Chiverton J, Wells K, Lewis E, Chen C, Podda B, Johnson D (2007) Statistical morphological skull stripping of adult and infant MRI data., Comput Biol Med 37 (3) pp. 342-357
This paper describes a novel automatic statistical morphology skull stripper (SMSS) that uniquely exploits a statistical self-similarity measure and a 2-D brain mask to delineate the brain. The result of applying SMSS to 20 MRI data set volumes, including scans of both adult and infant subjects is also described. Quantitative performance assessment was undertaken with the use of brain masks provided by a brain segmentation expert. The performance is compared with an alternative technique known as brain extraction tool. The results suggest that SMSS is capable of skull-stripping neurological data with small amounts of over- and under-segmentation.
Cabello J, Bailey A, Kitchen I, Guy M, Wells K (2009) Segmentation of low contrast-to-noise ratio images applied to functional imaging using adaptive region growing, Proceedings of SPIE: Posters: Segmentation 7259
Segmentation in medical imaging plays a critical role easing the delineation of key anatomical functional structures in all the imaging modalities. However, many segmentation approaches are optimized with the assumption of high contrast, and then fail when segmenting poor contrast to noise objects. The number of approaches published in the literature falls dramatically when functional imaging is the aim. In this paper a feature extraction based approach, based on region growing, is presented as a segmentation technique suitable for poor quality (low Contrast to Noise Ratio CNR) images, as often found in functional images derived from Autoradiography. The region growing combines some modifications from the typical region growing method, to make the algorithm more robust and more reliable. Finally the algorithm is validated using synthetic images and biological imagery.
Yip M, MacKenzie A, Lewis E, Dance DR, Young KC, Christmas W, Wells K (2011) Image resampling effects in mammographic image simulation, Physics in Medicine and Biology 56 (22)
This work describes the theory of resampling effects within the context of image simulation for mammographic images. The process of digitization associated with using digital imaging technology needs to be correctly addressed in any image simulation process. Failure to do so can lead to overblurring in the final synthetic image. A method for weighted neighbourhood averaging is described for non-integer scaling factors in resampling images. The use of the method is demonstrated by comparing simulated and real images of an edge test object acquired on two clinical mammography systems. Images were simulated using two setups: from idealized images and from images obtained with clinical systems. A Gaussian interpolation method is proposed as a single-step solution to modelling blurring filters for the simulation process. © 2011 Institute of Physics and Engineering in Medicine.
Allinson N, Anaxagoras T, Aveyard J, Arvanitis C, Bates R, Blue A, Bohndiek S, Cabello J, Chen L, Chen S, Clark A, Clayton C, Cook E, Cossins A, Crooks J, El-Gomati M, Evans PM, Faruqi W, French M, Gow J, Greenshaw T, Greig T, Guerrini N, Harris EJ, Henderson R, Holland A, Jeyasundra G, Karadaglic D, Konstantinidis A, Liang HX, Maini KMS, McMullen G, Olivo A, O'Shea V, Osmond J, Ott RJ, Prydderch M, Qiang L, Riley G, Royle G, Segneri G, Speller R, Symonds-Tayler JRN, Triger S, Turchetta R, Venanzi C, Wells K, Zha X, Zin H (2009) The Multidimensional Integrated Intelligent Imaging project (MI-3), NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 604 (1-2) pp. 196-198 ELSEVIER SCIENCE BV
Gutierrez DR, Montesdeoca OD, Santana AM, Wells K, Mendichovszky I, Gordon I (2007) MR-based renography as a replacement for radionuclide diagnostic studies, 2007 IEEE NUCLEAR SCIENCE SYMPOSIUM CONFERENCE RECORD, VOLS 1-11 pp. 4556-4563 IEEE
Rahni AAA, Lewis E, Wells K (2013) Characterisation of respiratory motion extracted from 4D MRI, Progress in Biomedical Optics and Imaging - Proceedings of SPIE 8669
Nuclear Medicine (NM) imaging is currently the most sensitive approach for functional imaging of the human body. However, in order to achieve high-resolution imaging, one of the factors degrading the detail or apparent resolution in the reconstructed image, namely respiratory motion, has to be overcome. All respiratory motion correction approaches depend on some assumption or estimate of respiratory motion. In this paper, the respiratory motion found from 4D MRI is analysed and characterised. The characteristics found are compared with previous studies and will be incorporated into the process of estimating respiratory motion. © 2013 SPIE.
Esposito M, Wells K, Anaxagoras T, Allinson NM, Larner J (2013) C autoradiography with a novel wafer scale CMOS Active Pixel Sensor, Journal of Instrumentation 8 (1)
C autoradiography is a well established technique for structural and metabolic analysis of cells and tissues. The most common detection medium for this application is film emulsion, which offers unbeatable spatial resolution due to its fine granularity but at the same time has some limiting drawbacks such as poor linearity and rapid saturation. In recent years several digital detectors have been developed, following the technological transition from analog to digital-based detection systems in the medical and biological field. Even so such digital systems have been greatly limited by the size of their active area (a few square centimeters), which have made them unsuitable for routine use in many biological applications where sample areas are typically
Cabello J, Wells K (2009) A Monte Carlo study on the spatial resolution of uncollimated ² particles with silicon-based detectors for autoradiography, IEEE Nuclear Science Symposium Conference Record pp. 2877-2881
Traditional Autoradiography is an imaging modality used in life sciences where thin ex-vivo tissue sections are placed in direct contact with autoradiographic film. High resolution autoradiograms can be obtained using low energy radioisotopes, such as 3H where an intrinsic 0.1-1 ¼m spatial resolution can be achieved due to limited ²- path length. Several digital alternatives have been presented in recent years to replace conventional film as the imaging medium, but the spatial resolution of film remains unmatched. Although silicon-based imaging technologies have demonstrated higher sensitivity compared to conventional film, the main issue that remains is spatial resolution. We address this here with an investigation into the design parameters that impact on spatial resolution when imaging uncollimated ²-found in Autoradiography. The study considers Monte Carlo simulation of the energy deposition process, the charge diffusion process in silicon and the detector noise, and this is applied to a range of radioisotope ² energies typically used in Autoradiography. Finally an optimal detector geometry to obtain the best possible spatial resolution for a specific technology and a specific radioisotope is suggested. ©2009 IEEE.
Wells K, Tumian A, Zapros A, Alnafea M, Saripan MI, Guy M, Hinton P (2005) Optimal energy window selection for scintigraphy & emission computed tomography, 2005 IEEE Nuclear Science Symposium Conference Record, Vols 1-5 pp. 2049-2053 IEEE
Elangovan P, Alrehily F, Pinto RF, Rashidnasab A, Dance DR, Young KC, Wells K (2016) Simulation of spiculated breast lesions, MEDICAL IMAGING 2016: PHYSICS OF MEDICAL IMAGING 9783 SPIE-INT SOC OPTICAL ENGINEERING
Saripan MI, Mohd Saad WH, Hashim S, Rahman ATA, Wells K, Bradley DA (2013) Analysis of photon scattering trends for material classification using artificial neural network models, IEEE Transactions on Nuclear Science 60 (2) pp. 515-519
In this project, we concentrate on using the Artificial Neural Network (ANN) approach to analyze the photon scattering trend given by specific materials. The aim of this project is to fully utilize the scatter components of an interrogating gamma-ray radiation beam in order to determine the types of material embedded in sand and later to determine the depth of the material. This is useful in a situation in which the operator has no knowledge of potentially hidden materials. In this paper, the materials that we used were stainless steel, wood and stone. These moderately high density materials are chosen because they have strong scattering components, and provide a good starting point to design our ANN model. Data were acquired using the Monte Carlo N-Particle Code, MCNP5. The source was a collimated pencil-beam projection of 1 MeV energy gamma rays and the beam was projected towards a slab of unknown material that was buried in sand. The scattered photons were collected using a planar surface detector located directly above the sample. In order to execute the ANN model, several feature points were extracted from the frequency domain of the collected signals. For material classification work, the best result was obtained for stone with 86.6% accurate classification while the most accurate buried distance is given by stone and wood, with a mean absolute error of 0.05. © 1963-2012 IEEE.
Yip M, Alsager A, Lewis E, Wells K, Young KC, Krupinski EA (2008) Validation of a digital mammography image simulation chain with automated scoring of CDMAM images, DIGITAL MAMMOGRAPHY, PROCEEDINGS 5116 pp. 409-416 SPRINGER-VERLAG BERLIN
A wide variety of digital mammography systems are available for breast cancer imaging, each varying in physical performance. However, the relationship between physical performance assessment and clinical outcome is not clear. Thus, a means of simulating technically and clinically realistic images from different systems would represent a first step towards elucidating the impact of physical performance on clinical outcome. To this end, a framework for simulating technically realistic images has been developed. A range of simulated test objects, including CDMAM have been used to determine whether the simulation chain correctly reproduces these objects thus validating the simulation framework. Results evaluated for two digital mammography systems have been promising, with simulated images proving similar to experimental images for Modulation Transfer Function and Normalised Noise Power Spectrum measurements differing by approximately 3%.
Rahni AAA, Lewis E, Wells K, Jones J (2012) Respiratory motion estimation in nuclear medicine imaging using a kernel model-based particle filter framework, IEEE Nuclear Science Symposium Conference Record pp. 2928-2932
The continual improvement in spatial resolution of Nuclear Medicine (NM) scanners has made accurate compensation of patient motion increasingly important. A major source of corrupting motion in NM acquisition is due to respiration. Therefore a particle filter (PF) approach has been proposed as a powerful method for motion correction in NM. The probabilistic view of the system in the PF has an advantage in that it considers the complexity and uncertainties of respiratory motion. Tests using the XCAT phantom have previously shown the possibility of estimating unseen organ configurations using training data that only consist of a single respiratory cycle. This paper builds upon previous work in two ways: (i) this is the first evaluation of a PF framework using clinical 4D thoracic CT data; and, (ii) this implementation uses a kernel density estimation (KDE) representation for the transition model, thus taking advantage of the PF's ability to use a wider range of stochastic models. The results show some improvement with the use of a KDE-based transition model and indicates that the PF should be applicable to clinical data. © 2011 IEEE.
Wells K, Bradley DA (2012) A review of X-ray explosives detection techniques for checked baggage., Appl Radiat Isot 70 (8) pp. 1729-1746
In recent times, the security focus for civil aviation has shifted from hijacking in the 1980s, towards deliberate sabotage. X-ray imaging provides a major tool in checked baggage inspection, with various sensitive techniques being brought to bear in determining the form, and density of items within luggage as well as other material dependent parameters. This review first examines the various challenges to X-ray technology in securing a safe system of passenger transportation. An overview is then presented of the various conventional and less conventional approaches that are available to the airline industry, leading to developments in state-of-the-art imaging technology supported by enhanced machine and observer-based decision making principles.
Wells K, Chiverton J, Partridge M, Barry M, Kadhem H, Ott B (2005) The partial volume effect in PET/SPECT and Benford's law, 2005 IEEE Nuclear Science Symposium Conference Record, Vols 1-5 pp. 1804-1808 IEEE
Esposito M, Bailey A, Newcombe J, Anaxagoras T, Allinson NM, Wells K (2012) CMOS APS in pre-clinical science: Next generation disruptive technology for multi-modality imaging, IEEE Nuclear Science Symposium Conference Record pp. 1910-1913
A new large area CMOS Active Pixel Sensor has been developed as single platform technology to be used across a range of ionizing and non-ionizing imaging applications in preclinical science, ranging from imaging of protein sequences to functional analysis of radio-labeled tissue sections.We present the first images of chemiluminescence detection in western blotting with a room temperature CMOS APS. Detection performance in western blotting have been compared with the gold standard detection medium, film emulsion, showing higher dynamic range and sensitivity with this new device. We also report on our first images of [125I]Epibatidine autoradiography of brain sections using a novel large area CMOS APS. © 2012 IEEE.
Diaz O, Dance DR, Young KC, Elangovan P, Bakic PR, Wells K (2014) Estimation of scattered radiation in digital breast tomosynthesis, Physics in Medicine and Biology 59 (15) pp. 4375-4390
Digital breast tomosynthesis (DBT) is a promising technique to overcome the tissue superposition limitations found in planar 2D x-ray mammography. However, as most DBT systems do not employ an anti-scatter grid, the levels of scattered radiation recorded within the image receptor are significantly higher than that observed in planar 2D x-ray mammography. Knowledge of this field is necessary as part of any correction scheme and for computer modelling and optimisation of this examination. Monte Carlo (MC) simulations are often used for this purpose, however they are computationally expensive and a more rapid method of calculation is desirable. This issue is addressed in this work by the development of a fast kernel-based methodology for scatter field estimation using a detailed realistic DBT geometry. Thickness-dependent scatter kernels, which were validated against the literature with a maximum discrepancy of 4% for an idealised geometry, have been calculated and a new physical parameter (air gap distance) was used to estimate more accurately the distribution of scattered radiation for a series of anthropomorphic breast phantom models. The proposed methodology considers, for the first time, the effects of scattered radiation from the compression paddle and breast support plate, which can represent more than 30% of the total scattered radiation recorded within the image receptor. The results show that the scatter field estimator can calculate scattered radiation images in an average of 80 min for projection angles up to 25° with equal to or less than a 10% error across most of the breast area when compared with direct MC simulations. © 2014 Institute of Physics and Engineering in Medicine.
Jones J, Lewis E, Abd Rahni A, Wells K, Ezhil V (2012) Mosaics of polynomial transformations giving a patient specific registration to reduce breathing motion artefacts, IEEE Nuclear Science Symposium Conference Record pp. 3066-3072
Nuclear Medicine (NM) imaging is an important diagnostic tool, used widely in the field of oncology amongst others. However, NM images suffer from significant blurring due to inevitable patient motion, such as breathing, coughing and other voluntary or involuntary movement. Advances in detector technology and reconstruction techniques have led to a steady improvement in NM spatial resolution and the problems posed by patient motion are therefore becoming increasingly significant, particularly for PET/CT. Many correction schemes will require gated images to be aligned. This paper describes a method of registering major organs in piecewise fashion called virtual dissection. Results from processing synthetic data and one set of patient data are presented. A key feature is the possibility to use a mixture of registration techniques on a single set of data and combine the results into a single set of output images. © 2011 IEEE.
Elangovan P, Rashidnasab A, Mackenzie A, Dance DR, Young KC, Bosmans H, Segars WP, Wells K (2015) Performance Comparison of Breast Imaging Modalities using a 4AFC Human Observer Study, MEDICAL IMAGING 2015: PHYSICS OF MEDICAL IMAGING 9412 SPIE-INT SOC OPTICAL ENGINEERING
Tahavori F, Alnowami M, Wells K (2012) A comparison between adaptive kernel density estimation and Gaussian Mixture Regression for real-time tumour motion prediction from external surface motion, IEEE Nuclear Science Symposium Conference Record pp. 3902-3905 IEEE
In this present study, tumour (3D) locations are predicted via external surface motion, extracted from abdomen/ thoracic surface measurements that can be used to enhance dose targeting in external beam radiotherapy. Canonical Correlation Analysis (CCA) is applied to the surface and tumour motion data to maximise the correlation between them. This correlation is exploited for motion prediction [1]. Nine dynamic CT datasets were used to extract the surface and tumour motion and to create the Canonical Correlation model (CCM). Gaussian Mixture Regression (GMR) and Adaptive Kernel Density Estimation (AKDE) were trained on these nine datasets to predict the respiratory signal by updating the surface motion and CCM. A leave-one-out method was used to evaluate and compare the performance of GMR and AKDE in predicting the tumour motion. © 2012 IEEE.
Cabello J, Wells K, Metaxas A, Bailey A, Kitchen I (2009) Elastic atlas registration of ²- autoradiograms using scattered data interpolators, IEEE Nuclear Science Symposium Conference Record pp. 3700-3704 IEEE
Autoradiography is a widely extended pre-clinical nuclear imaging modality used in life sciences to investigate and localise radiolabelled biological pathways in thin ex-vivo tissue sections. After the tissue section has been exposed to an ionising radiation detector the resulting labelled regions are subsequently analysed. Typically, the resulting autoradiograms are analysed manually by an expert life scientists using a visual template as reference to measure the different radioligand uptake levels in the different areas of, in our case, mouse brain. This process is extremely time consuming and error prone, with the expertise of the life scientist playing a significant role. In this paper we describe a semi-automatic method to register a template brain atlas on to the brain autoradiogram making the analysis process more efficient, repeatable and independent of the expertise of the life scientist. The method first identifies those regions with high and low level of radioligand uptake by region growing segmentation. Subsequently, the counterpart regions in the corresponding atlas image are manually identified. Finally a set of control points is extracted from each region contour in the autoradiogram and the atlas image to apply a scattered data interpolator. ©2009 IEEE.
Bradley DA, Hashim S, Saripan MI, Wells K, Dunn WL (2011) Photon signature analysis using template matching, Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 652 (1) pp. 466-469 Elsevier
Cabello J, Bailey A, Kitchen I, Prydderch M, Clark A, Turchetta R, Wells K (2007) Digital autoradiography using room temperature CCD and CMOS imaging technology, Physics in Medicine and Biology 52 (16) pp. 4993-5011
CCD (charged coupled device) and CMOS imaging technologies can be applied to thin tissue autoradiography as potential imaging alternatives to using conventional film. In this work, we compare two particular devices: a CCD operating in slow scan mode and a CMOS-based active pixel sensor, operating at near video rates. Both imaging sensors have been operated at room temperature using direct irradiation with images produced from calibrated microscales and radiolabelled tissue samples. We also compare these digital image sensor technologies with the use of conventional film. We show comparative results obtained with 14C calibrated microscales and 35S radiolabelled tissue sections. We also present the first results of 3H images produced under direct irradiation of a CCD sensor operating at room temperature. Compared to film, silicon-based imaging technologies exhibit enhanced sensitivity, dynamic range and linearity. © 2007 IOP Publishing Ltd.
Rodriguez Gutierrez D, Wells K, Diaz Montesdeoca O, Moran Santana A, Mendichovszky IA, Gordon I (2010) Partial volume effects in dynamic contrast magnetic resonance renal studies, European Journal of Radiology 75 (2) pp. 221-229
Smith R, Rahni AAA, Jones J, Tahavori F, Wells K (2014) Motion estimation for nuclear medicine: A probabilistic approach, Progress in Biomedical Optics and Imaging - Proceedings of SPIE 9034
Accurate, Respiratory Motion Modelling of the abdominal-thoracic organs serves as a pre-requisite for motion correction of Nuclear Medicine (NM) Images. Many respiratory motion models to date build a static correspondence between a parametrized external surrogate signal and internal motion. Mean drifts in respiratory motion, changes in respiratory style and noise conditions of the external surrogate signal motivates a more adaptive approach to capture non-stationary behavior. To this effect we utilize the application of our novel Kalman model with an incorporated expectation maximization step to allow adaptive learning of model parameters with changing respiratory observations. A comparison is made with a popular total least squares (PCA) based approach. It is demonstrated that in the presence of noisy observations the Kalman framework outperforms the static PCA model, however, both methods correct for respiratory motion in the computational anthropomorphic phantom to
Mackenzie A, Dance DR, Workman A, Yip M, Wells K, Young KC (2012) Conversion of mammographic images to appear with the noise and sharpness characteristics of a different detector and x-ray system., Med Phys 39 (5) pp. 2721-2734
PURPOSE: Undertaking observer studies to compare imaging technology using clinical radiological images is challenging due to patient variability. To achieve a significant result, a large number of patients would be required to compare cancer detection rates for different image detectors and systems. The aim of this work was to create a methodology where only one set of images is collected on one particular imaging system. These images are then converted to appear as if they had been acquired on a different detector and x-ray system. Therefore, the effect of a wide range of digital detectors on cancer detection or diagnosis can be examined without the need for multiple patient exposures. METHODS: Three detectors and x-ray systems [Hologic Selenia (ASE), GE Essential (CSI), Carestream CR (CR)] were characterized in terms of signal transfer properties, noise power spectra (NPS), modulation transfer function, and grid properties. The contributions of the three noise sources (electronic, quantum, and structure noise) to the NPS were calculated by fitting a quadratic polynomial at each spatial frequency of the NPS against air kerma. A methodology was developed to degrade the images to have the characteristics of a different (target) imaging system. The simulated images were created by first linearizing the original images such that the pixel values were equivalent to the air kerma incident at the detector. The linearized image was then blurred to match the sharpness characteristics of the target detector. Noise was then added to the blurred image to correct for differences between the detectors and any required change in dose. The electronic, quantum, and structure noise were added appropriate to the air kerma selected for the simulated image and thus ensuring that the noise in the simulated image had the same magnitude and correlation as the target image. A correction was also made for differences in primary grid transmission, scatter, and veiling glare. The method was validated by acquiring images of a CDMAM contrast detail test object (Artinis, The Netherlands) at five different doses for the three systems. The ASE CDMAM images were then converted to appear with the imaging characteristics of target CR and CSI detectors. RESULTS: The measured threshold gold thicknesses of the simulated and target CDMAM images were closely matched at normal dose level and the average differences across the range of detail diameters were -4% and 0% for the CR and CSI systems, r
Rashidnasab A, Elangovan P, Dance DR, Young KC, Yip M, Diaz O, Wells K (2012) Realistic simulation of breast mass appearance using random walk, MEDICAL IMAGING 2012: PHYSICS OF MEDICAL IMAGING 8313 SPIE-INT SOC OPTICAL ENGINEERING
Rahni AAA, Rahni AAA, Lewis E, Wells K, Wells K, Jones J (2012) Respiratory motion estimation in nuclear medicine imaging using a kernel model-based particle filter framework, IEEE Nuclear Science Symposium Conference Record pp. 2928-2932
The continual improvement in spatial resolution of Nuclear Medicine (NM) scanners has made accurate compensation of patient motion increasingly important. A major source of corrupting motion in NM acquisition is due to respiration. Therefore a particle filter (PF) approach has been proposed as a powerful method for motion correction in NM. The probabilistic view of the system in the PF has an advantage in that it considers the complexity and uncertainties of respiratory motion. Tests using the XCAT phantom have previously shown the possibility of estimating unseen organ configurations using training data that only consist of a single respiratory cycle. This paper builds upon previous work in two ways: (i) this is the first evaluation of a PF framework using clinical 4D thoracic CT data; and, (ii) this implementation uses a kernel density estimation (KDE) representation for the transition model, thus taking advantage of the PF's ability to use a wider range of stochastic models. The results show some improvement with the use of a KDE-based transition model and indicates that the PF should be applicable to clinical data. © 2011 IEEE.
Cabello J, Wells K (2010) The spatial resolution of silicon-based electron detectors in ²-autoradiography, Physics in Medicine and Biology 55 (6) pp. 1677-1699
Thin tissue autoradiography is an imaging modality where ex-vivo tissue sections are placed in direct contact with autoradiographic film. These tissue sections contain a radiolabelled ligand bound to a specific biomolecule under study. This radioligand emits ² - or ²+ particles ionizing silver halide crystals in the film. High spatial resolution autoradiograms are obtained using low energy radioisotopes, such as 3H where an intrinsic 0.1-1 ½m spatial resolution can be achieved. Several digital alternatives have been presented over the past few years to replace conventional film but their spatial resolution has yet to equal film, although silicon-based imaging technologies have demonstrated higher sensitivity compared to conventional film. It will be shown in this work how pixel size is a critical parameter for achieving high spatial resolution for low energy uncollimated beta imaging. In this work we also examine the confounding factors impeding silicon-based technologies with respect to spatial resolution. The study considers charge diffusion in silicon and detector noise, and this is applied to a range of radioisotopes typically used in autoradiography. Finally an optimal detector geometry to obtain the best possible spatial resolution for a specific technology and a specific radioisotope is suggested. © 2010 Institute of Physics and Engineering in Medicine.
Elangovan P, MacKenzie A, Diaz O, Rashidnasab A, Dance DR, Young KC, Warren LM, Shaheen E, Bosmans H, Bakic PR, Wells K (2012) A modelling framework for evaluation of 2D-mammography and breast tomosynthesis systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7361 LNCS pp. 338-345
Planar 2D X-ray mammography is the most common screening technique used for breast cancer detection. Digital breast tomosynthesis (DBT) is a new and emerging technology that overcomes some of the limitations of conventional planar imaging. However, it is important to understand the impact of these two modalities on cancer detection rates and patient recall. Since it is difficult to adequately evaluate different modalities clinically, a collection of modeling tools is introduced in this paper that can be used to emulate the image acquisition process for both modalities. In this paper, we discuss image simulation chains that can be used for the evaluation of 2D-mammography and DBT systems in terms of both technical factors and observer studies. © 2012 Springer-Verlag Berlin Heidelberg.
Gutierrez DR, Wells K, Montesdeoca OD, Santana AM, Mendichovszky IA, Gordon I (2010) Partial volume effects in dynamic contrast magnetic resonance renal studies, EUR J RADIOL 75 (2) pp. 221-229 ELSEVIER IRELAND LTD
This is the first study of partial volume effect in quantifying renal function on dynamic contrast enhanced magnetic resonance imaging. Dynamic image data were acquired for a cohort of 10 healthy volunteers. Following respiratory motion correction, each voxel location was assigned a mixing vector representing the 'overspilling' contributions of each tissue due to the convolution action of the imaging system's point spread function. This was used to recover the true intensities associated with each constituent tissue. Thus, non-renal contributions from liver, spleen and other surrounding tissues could be eliminated from the observed time-intensity curves derived from a typical renal cortical region of interest. This analysis produced a change in the early slope of the renal curve, which subsequently resulted in an enhanced glomerular filtration rate estimate. This effect was consistently observed in a Rutland-Patlak analysis of the time-intensity data: the volunteer cohort produced a partial volume effect corrected mean enhancement of 36% in relative glomerular filtration rate with a mean improvement of 7% in r(2) fitting of the Rutland-Patlak model compared to the same analysis undertaken without partial volume effect correction. This analysis strongly supports the notion that dynamic contrast enhanced magnetic resonance imaging of kidneys is substantially affected by the partial volume effect, and that this is a significant obfuscating factor in subsequent glomerular filtration rate estimation. (C) 2009 Elsevier Ireland Ltd. All rights reserved.
Esposito M, Newcombe J, Wells K (2011) Western Blotting Electrophoretic Sequencing:
First Images with a Room Temperature
CMOS Detector,
Proceedings of IEEE Nuclear Science Symposium and Medical Imaging Conference pp. 2491-2494 IEEE
CMOS imaging technology can be applied to Chemiluminescence
Western Blotting as a potential imaging alternative
technology to using conventional film-emulsion. In this work
the authors present a through investigation on the performance
of CMOS Active Pixel Sensors for using in western blotting.
Chemiluminescence labeling is a well established technique to
detect proteins and presents several advantages compared with
the fluorescence labeling. In fact it requires neither external illumination
nor filtering optics and does not produce an inherently
label-related background to correct. In this paper the first results
of imaging a secondary antibody labeled with chemiluminescence
reagents obtained with a CMOS sensor operating at room
temperature are presented
Chiverton JP, Wells K (2008) Adaptive partial volume classification of MRI data, Physics in Medicine and Biology 53 (20) pp. 5577-5594
Tomographic biomedical images are commonly affected by an imaging artefact known as the partial volume (PV) effect. The PV effect produces voxels composed of a mixture of tissues in anatomical magnetic resonance imaging (MRI) data resulting in a continuity of these tissue classes. Anatomical MRI data typically consist of a number of contiguous regions of tissues or even contiguous regions of PV voxels. Furthermore discontinuities exist between the boundaries of these contiguous image regions. The work presented here probabilistically models the PV effect using spatial regularization in the form of continuous Markov random fields (MRFs) to classify anatomical MRI brain data, simulated and real. A unique approach is used to adaptively control the amount of spatial regularization imposed by the MRF. Spatially derived image gradient magnitude is used to identify the discontinuities between image regions of contiguous tissue voxels and PV voxels, imposing variable amounts of regularization determined by simulation. Markov chain Monte Carlo (MCMC) is used to simulate the posterior distribution of the probabilistic image model. Promising quantitative results are presented for PV classification of simulated and real MRI data of the human brain. © 2008 Institute of Physics and Engineering in Medicine.
Cabello J, Bailey A, Kitchen I, Clark A, Crooks J, Halsall R, Key-Charriere M, Martin S, Prydderch M, Turchetta R, Wells K (2007) Digital autoradiography using CCD and CMOS imaging technology, 2006 IEEE NUCLEAR SCIENCE SYMPOSIUM CONFERENCE RECORD, VOL 1-6 pp. 2607-2612 IEEE
Alnowami M, Lewis E, Wells K, Guy M (2010) Inter- and intra-subject variation of abdominal vs. thoracic respiratory motion using kernel density estimation, IEEE Nuclear Science Symposium Conference Record (NSS/MIC) pp. 2921-2924
In nuclear medicine, there is a significant research focus in developing a new approach in monitoring, tracking and compensating respiratory motion during image acquisition. We address this by attempting to model the respiratory cycle pattern and finding a method that describes the configuration of the anterior surface which then correlates with the internal position/configuration of the internal organ as a foundation for motion compensation. This paper presents novel work in parameterizing external respiratory motion using a method based on the variation of abdominal vs. thoracic surface markers to investigate inter- and intra-subject variation. The dominant mode of variation of the Abdominal and Thoracic surfaces during respiration using Principle Component Analysis (PCA) is studied. This demonstrates that pattern of TS vs AS motion appears temporally at a global level stable. Thus although breathing style is consistent within a given subject, we there observe temporal changes in the amplitude and density of the PDF in intra-subject data.
Cabello J, Wells K, Bailey A, Kitchen I (2007) Semi-automatic elastic registration applied to a beta-autoradiography brain atlas, 2007 IEEE NUCLEAR SCIENCE SYMPOSIUM CONFERENCE RECORD, VOLS 1-11 pp. 4303-4307 IEEE
Grenier N, Mendichovszky L, De Senneville BD, Rouiol S, Desbarats P, Pedersen M, Wells K, Frokiaer J, Gordon I (2008) Measurement of glomerular filtration rate with magnetic resonance imaging: Principles, limitations, and expectations, SEMINARS IN NUCLEAR MEDICINE 38 (1) pp. 47-55 W B SAUNDERS CO-ELSEVIER INC
Esposito M, Anaxagoras T, Konstantinidis AC, Zheng Y, Speller RD, Evans PM, Allinson NM, Wells K (2014) Performance of a novel wafer scale CMOS active pixel sensor for bio-medical imaging, Physics in Medicine and Biology 59 (13) pp. 3533-3554
Recently CMOS active pixels sensors (APSs) have become a valuable alternative to amorphous silicon and selenium flat panel imagers (FPIs) in bio-medical imaging applications. CMOS APSs can now be scaled up to the standard 20cm diameter wafer size by means of a reticle stitching block process. However, despite wafer scale CMOS APS being monolithic, sources of non-uniformity of response and regional variations can persist representing a significant challenge for wafer scale sensor response. Non-uniformity of stitched sensors can arise from a number of factors related to the manufacturing process, including variation of amplification, variation between readout components, wafer defects and process variations across the wafer due to manufacturing processes. This paper reports on an investigation into the spatial non-uniformity and regional variations of a wafer scale stitched CMOS APS. For the first time a per-pixel analysis of the electro-optical performance of a wafer CMOS APS is presented, to address inhomogeneity issues arising from the stitching techniques used to manufacture wafer scale sensors. A complete model of the signal generation in the pixel array has been provided and proved capable of accounting for noise and gain variations across the pixel array. This novel analysis leads to readout noise and conversion gain being evaluated at pixel level, stitching block level and in regions of interest, resulting in a coefficient of variation 1.9%. The uniformity of the image quality performance has been further investigated in a typical x-ray application, i.e. mammography, showing a uniformity in terms of CNR among the highest when compared with mammography detectors commonly used in clinical practice. Finally, in order to compare the detection capability of this novel APS with the technology currently used (i.e. FPIs), theoretical evaluation of the detection quantum efficiency (DQE) at zero-frequency has been performed, resulting in a higher DQE for this detector compared to FPIs. Optical characterization, x-ray contrast measurements and theoretical DQE evaluation suggest that a trade off can be found between the need of a large imaging area and the requirement of a uniform imaging performance, making the DynAMITe large area CMOS APS suitable for a range of bio-medical applications. © 2014 Institute of Physics and Engineering in Medicine.
Jones J, Lewis E, Abd Rahni A, Ezhil V, Wells K (2012) Mosaics of polynomial transformations giving a patient specific registration to reduce breathing motion artefacts, IEEE Nuclear Science Symposium Conference Record pp. 3066-3072
Nuclear Medicine (NM) imaging is an important diagnostic tool, used widely in the field of oncology amongst others. However, NM images suffer from significant blurring due to inevitable patient motion, such as breathing, coughing and other voluntary or involuntary movement. Advances in detector technology and reconstruction techniques have led to a steady improvement in NM spatial resolution and the problems posed by patient motion are therefore becoming increasingly significant, particularly for PET/CT. Many correction schemes will require gated images to be aligned. This paper describes a method of registering major organs in piecewise fashion called virtual dissection. Results from processing synthetic data and one set of patient data are presented. A key feature is the possibility to use a mixture of registration techniques on a single set of data and combine the results into a single set of output images. © 2011 IEEE.
Cabello J, Wells K (2007) A Monte Carlo investigation into the fundamental limitations of digital beta-autoradiography: Considerations for detector design, 2007 IEEE NUCLEAR SCIENCE SYMPOSIUM CONFERENCE RECORD, VOLS 1-11 pp. 3625-3630 IEEE
Diaz O, Dance DR, Young KC, Elangovan P, Bakic PR, Wells K (2012) A fast scatter field estimator for Digital Breast Tomosynthesis, MEDICAL IMAGING 2012: PHYSICS OF MEDICAL IMAGING 8313 SPIE-INT SOC OPTICAL ENGINEERING
Loveland J, Gundogdu O, Morton E, Wells K, Bradley DA (2010) Phase contrast imaging: Effect of increased object-detector distances at X-ray diagnostic and megavoltage energies, Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
Alnowami M, Alnwaimi B, Tahavori F, Copland M, Wells K (2012) A Quantitative Assessment of using the Kinect for Xbox360 (TM) For Respiratory Surface Motion Tracking, MEDICAL IMAGING 2012: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING 8316 SPIE-INT SOC OPTICAL ENGINEERING
Yip M, Rodriguez D, Lewis E, Wells K, Young KC (2007) A simulation framework for the comparison of digital mammography imaging technology, 2007 IEEE NUCLEAR SCIENCE SYMPOSIUM CONFERENCE RECORD, VOLS 1-11 pp. 3635-3639 IEEE
Ashrani AA, Lewis E, Wells K (2013) Recursive Bayesian estimation of respiratory motion using a modified autoregressive transition model, Progress in Biomedical Optics and Imaging - Proceedings of SPIE 8669
Compensation for respiratory motion has been identified as a crucial factor in achieving high resolution Nuclear Medicine (NM) imaging. Many motion correction approaches have been studied and they are seen to have advantages over simpler approaches such as respiratory gating. However, all motion correction approaches rely on an assumption or estimation of respiratory motion. This paper builds upon previous work in recursive Bayesian estimation of respiratory motion assuming a stereo camera observation of the motion of the external torso surface. This paper compares the performance of a modified autoregressive transition model against the previously presented linear transition model used when estimating motion within a 4D dataset generated from the XCAT phantom. © 2013 SPIE.
Chiverton J, Wells K (2006) Mixture effects in FIR low-pass filtered signals, IEEE SIGNAL PROCESSING LETTERS 13 (6) pp. 369-372 IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Alnafea M, Wells K, Spyrou NM, Guy M (2007) Preliminary Monte Carlo study of coded aperture imaging with a CZT gamma camera system for scintimammography, NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 573 (1-2) pp. 122-125 ELSEVIER SCIENCE BV
Smith RL, Wells K, Jones J, Dasari P, Lindsay C, King M (2013) Toward a framework for high resolution parametric respiratory motion modelling, IEEE Nuclear Science Symposium Conference Record
A framework to facilitate the realization of dynamic MRI data with simultaneously increased temporal and spatial resolution is proposed. Deformable registration to a reference frame of spatially sparse, high temporally resolved two dimensional sagittal slices acquired sequentially across a volunteers lateral dimension serve as a subset of incomplete observation of full three dimensional vector fields. Registration of an averaged, re-binned, single respiratory cycle with full spatial sampling serves as a basis for estimation of full three dimensional vector fields derived from the sparse subset. The inverse of the estimated full 3D vector fields from sparse measurements allows propagation of a high resolution, re binned static volume with breathing modes derived from the sparse dynamic data. Proof of concept experiments are undertaken with the anthropomorphic XCAT phantom. A quantitative evaluation of full vector fields derived from sparse samples in comparison to their ground truth results in a mean error of the order of 1mm. A qualitative assessment of the motion of a propagated high resolution static MRI volume is presented. © 2013 IEEE.
Wells K, Bradley DA (2012) A review of X-ray explosives detection techniques for checked baggage, Applied Radiation and Isotopes 70 (8) pp. 1729-1746
In recent times, the security focus for civil aviation has shifted from hijacking in the 1980s, towards deliberate sabotage. X-ray imaging provides a major tool in checked baggage inspection, with various sensitive techniques being brought to bear in determining the form, and density of items within luggage as well as other material dependent parameters. This review first examines the various challenges to X-ray technology in securing a safe system of passenger transportation. An overview is then presented of the various conventional and less conventional approaches that are available to the airline industry, leading to developments in state-of-the-art imaging technology supported by enhanced machine and observer-based decision making principles. © 2012 Elsevier Ltd.
Rashidnasab A, Elangovan P, Diaz O, Mackenzie A, Young K, Dance D, Wells K (2013) Simulation of 3D DLA masses in digital breast tomosynthesis, Progress in Biomedical Optics and Imaging - Proceedings of SPIE 8668
Digital breast tomosynthesis (DBT) is suggested to have superior performance compared to 2D mammography in terms of cancer visibility, especially in the case of dense breasts. However, the overall performance of tomosynthesis for screening applications, and the manner in which tomosynthesis should be optimally used for screening remains unclear. This motivates the development of software tools that can insert user-defined synthetic pathology of realistic appearance into clinical tomosynthesis images for subsequent use in virtual clinical trials. We present a method for inserting lesions grown using Diffusion Limited Aggregation, previously validated in 2D mammograms, into clinical DBT images. A preliminary pilot study was used to validate the realism of the masses, wherein three readers each viewed 19 cases and rated the realism of the inserted masses. Each case included a simulated mass inserted in the tomosynthesis projections and the counterpart digital 2D mammogram. These results show that masses can be successfully embedded in the tomosynthesis projections and can produce visually authentic DBT images containing synthetic pathology. These results will be used to further optimize the appearance of these masses in DBT for an upcoming validation. © 2013 SPIE.
Bradley DA, Wells K (2013) Reprint of: Biomedical applications reviewed: Hot topic areas, Radiation Physics and Chemistry
Making reference to the British Journal of Radiology and competitor journal titles, we look at the general area of biomedical physics, reviewing some of the associated topics in ionising radiation research attracting interest over the past 2 years. We also reflect on early developments that have paved the way for these endeavours. The talk is illustrated by referring to a number of biomedical physics areas in which this group has been directly involved, including novel imaging techniques that address compositional and structural makeup as well as use of elastically scattered X-ray phase contrast, radiation damage linking to possible pericardial effects in radiotherapy, simulation of microvascularity and oxygenation with a focus of radiation resistant hypoxic tumours, issues of high spatial resolution dosimetry and tissue interface radiotherapy with doses enhanced through use of high atomic number photoelectron conversion media. © 2013 Elsevier Ltd. All rights reserved.
Ashrani AA, Lewis E, Wells K (2013) Development of a semi-automated segmentation framework for thoracic-abdominal organs, IEEE ICSIPA 2013 - IEEE International Conference on Signal and Image Processing Applications pp. 232-236
Due to the increasing amount of data available from medical imaging procedures and also the increase in computing power, there has been a rise in the automation of the analysis of such data. A crucial step in the automation of such procedures is accurate segmentation of anatomy. Popular approaches include model based segmentation. However, these approaches require an atlas which may not be generic enough. This paper proposes a semi-automated data-driven segmentation framework of thoracic CT scans. The preliminary results of the framework is presented and discussed with proposals for future work. © 2013 IEEE.
Chiverton J, Wells K, Partridge M (2006) A Combined Noise Reduction and Partial Volume Estimation Method for Image Quantitation, 2006 IEEE NUCLEAR SCIENCE SYMPOSIUM CONFERENCE RECORD, VOL 1-6 pp. 3221-3228 IEEE
Kadhem H, Rodriguez D, Tena JR, Wells K, Lewis E, Guy M (2007) Ultra low dose CT attenuation correction maps for emission computed tomography, IEEE Nuclear Science Symposium Conference Record 4 pp. 2123-2127
We present a method for obtaining attenuation maps for use in emission computed tomography (ECT) using ultra low dose CT data (at 140kVp, down to 10mA). This is achieved using a recursive k-means clustering method, the output of which initializes successive parameter-less region growing procedures. The method automatically produces templates corresponding to bone, lung, soft and dense tissue (muscle and fat). The segmentation of each tissue class from k-means clustering is used to compensate for the higher statistical noise variation seen at lower dose. The use of the region grower provides local contextual information that minimizes the impact of global noise. The templates were assigned appropriate linear attenuation coefficients and then convolved with the PET/SPECT system's PSF. This approach was applied to a dataset from an experimental anthropomorphic phantom exposed to systematically reducing CT dose derived from an X-ray beam at 140kVp and varying current from 160mA (full diagnostic dose) to 10mA (ultra low dose). Preliminary results show that for the purpose of CT attenuation correction, it is possible to successfully produce attenuation maps at ultra low dose with very low error (compared to full diagnostic dose) if used with the segmentation method presented. © 2006 IEEE.
Rashidnasab A, Elangovan P, Mackenzie A, Dance DR, Young KC, Bosmans H, Wells K (2015) Virtual clinical trials using inserted pathology in clinical images: investigation of assumptions for local glandularity and noise, MEDICAL IMAGING 2015: PHYSICS OF MEDICAL IMAGING 9412 SPIE-INT SOC OPTICAL ENGINEERING
Bradley DA, Hashim S, Saripan MI, Wells K, Dunn WL (2011) Photon signature analysis using template matching, Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 652 (1) pp. 466-469
We describe an approach to detect improvised explosive devices (IEDs) by using a template matching procedure. This approach relies on the signature due to backstreaming ³ photons from various targets. In this work we have simulated cylindrical targets of aluminum, iron, copper, water and ammonium nitrate (nitrogen-rich fertilizer). We simulate 3.5 MeV source photons distributed on a plane inside a shielded area using Monte Carlo N-Particle (MCNPTM) code version 5 (V5). The 3.5 MeV source gamma rays yield 511 keV peaks due to pair production and scattered gamma rays. In this work, we simulate capture of those photons that backstream, after impinging on the target element, toward a NaI detector. The captured backstreamed photons are expected to produce a unique spectrum that will become part of a simple signal processing recognition system based on the template matching method. Different elements were simulated using different sets of random numbers in the Monte Carlo simulation. To date, the sum of absolute differences (SAD) method has been used to match the template. In the examples investigated, template matching was found to detect all elements correctly. © 2011 Elsevier B.V.
Elangovan P, Mackenzie A, Dance D, Young K, Cooke V, Wilkinson L, Given-Wilson R, Wallis M, Wells K (2017) Design and validation of realistic breast models for use in multiple alternative forced choice virtual clinical trials, PHYSICS IN MEDICINE AND BIOLOGY 62 (7) pp. 2778-2794 IOP PUBLISHING LTD
A novel method has been developed for generating quasi-realistic voxel phantoms which simulate the compressed breast in mammography and digital breast tomosynthesis (DBT). The models are suitable for use in virtual clinical trials requiring realistic anatomy which use the multiple alternative forced choice (AFC) paradigm and patches from the complete breast image. The breast models are produced by extracting features of breast tissue components from DBT clinical images including skin, adipose and fibro-glandular tissue, blood vessels and Cooper?s ligaments. A range of different breast models can then be generated by combining these components. Visual realism was validated using a receiver operating characteristic (ROC) study of patches from simulated images calculated using the breast models and from real patient images. Quantitative analysis was undertaken using fractal dimension and power spectrum analysis. The average areas under the ROC curves for 2D and DBT images were 0.51 ± 0.06 and 0.54 ± 0.09 demonstrating that simulated and real images were statistically indistinguishable by expert breast readers (7 observers); errors represented as one standard error of the mean. The average fractal dimensions (2D, DBT) for real and simulated images were (2.72 ± 0.01, 2.75 ± 0.01) and (2.77 ± 0.03, 2.82 ± 0.04) respectively; errors represented as one standard error of the mean. Excellent agreement was found between power spectrum curves of real and simulated images, with average ² values (2D, DBT) of (3.10 ± 0.17, 3.21 ± 0.11) and (3.01 ± 0.32, 3.19 ± 0.07) respectively; errors represented as one standard error of the mean. These results demonstrate that radiological images of these breast models realistically represent the complexity of real breast structures and can be used to simulate patches from mammograms and DBT images that are indistinguishable from patches from the corresponding real breast images. The method can generate about 500 radiological patches (~30mm × 30mm) per day for AFC experiments on a single workstation. This is the first study to quantitatively validate the realism of simulated radiological breast images using direct blinded comparison with real data via the ROC paradigm with expert breast readers
Hadjipanteli A, Elangovan P, Mackenzie A, Looney P, Wells K, Dance D, Young K (2017) The effect of system geometry and dose on the threshold detectable calcification diameter in 2D-mammography and digital breast tomosynthesis, PHYSICS IN MEDICINE AND BIOLOGY 62 (3) pp. 858-877 IOP PUBLISHING LTD
Digital breast tomosynthesis (DBT) is under consideration to replace or to be used in combination with 2D-mammography in breast screening. The aim of this study was the comparison of the detection of microcalcification clusters by human observers in simulated breast images using 2D-mammography, narrow angle (15°/15 projections) and wide angle (50°/25 projections) DBT. The effects of the cluster height in the breast and the dose to the breast on calcification detection were also tested. Simulated images of 6 cm thick compressed breasts were produced with and without microcalcification clusters inserted, using a set of image modelling tools for 2D-mammography and DBT. Image processing and reconstruction were performed using commercial software. A series of 4-alternative forced choice (4AFC) experiments was conducted for signal detection with the microcalcification clusters as targets. Threshold detectable calcification diameter was found for each imaging modality with standard dose: 2D-mammography: 2D-mammography (165 ± 9 µm), narrow angle DBT (211 ± 11 µm) and wide angle DBT (257 ± 14 µm). Statistically significant differences were found when using different doses, but different geometries had a greater effect. No differences were found between the threshold detectable calcification diameters at different heights in the breast. Calcification clusters may have a lower detectability using DBT than 2D imaging.
Tahavori F, Alnowami M, Wells K (2014) Marker-less respiratory motion modeling using the Microsoft Kinect for Windows, Progress in Biomedical Optics and Imaging - Proceedings of SPIE 9036
Patient respiratory motion is a major problem during external beam radiotherapy of the thoracic and abdominal regions due to the associated organ and target motion. In addition, such motion introduces uncertainty in both radiotherapy planning and delivery and may potentially vary between the planning and delivery sessions. The aim of this work is to examine subject-specific external respiratory motion and its associated drift from an assumed average cycle which is the basis for many respiratory motion compensated applications including radiotherapy treatment planning and delivery. External respiratory motion data were acquired from a group of 20 volunteers using a marker-less 3D depth camera, Kinect for Windows. The anterior surface encompassing thoracic and abdominal regions were subject to principal component analysis (PCA) to investigate dominant variations. The first principal component typically describes more than 70% of the motion data variance in the thoracic and abdominal surfaces. Across all of the subjects used in this study, 58% of subjects demonstrate largely abdominal breathing and 33% exhibited largely thoracic dominated breathing. In most cases there is observable drift in respiratory motion during the 300s capture period, which is visually demonstrated using Kernel Density Estimation. This study demonstrates that for this cohort of apparently healthy volunteers, there is significant respiratory motion drift in most cases, in terms of amplitude and relative displacement between the thoracic and abdominal respiratory components. This has implications for the development of effective motion compensation methodology. © 2014 SPIE.
Esposito M, Anaxagoras T, Fant A, Wells K, Konstantinidis A, Osmond JPF, Evans PM, Speller RD, Allinson NM (2011) DynAMITe: A wafer scale sensor for biomedical applications, Journal of Instrumentation 6 (12) C12064 IOP Publishing
In many biomedical imaging applications Flat Panel Imagers (FPIs) are currently the most common option. However, FPIs possess several key drawbacks such as large pixels, high noise, low frame rates, and excessive image artefacts. Recently Active Pixel Sensors (APS) have gained popularity overcoming such issues and are now scalable up to wafer size by appropriate reticule stitching. Detectors for biomedical imaging applications require high spatial resolution, low noise and high dynamic range. These figures of merit are related to pixel size and as the pixel size is fixed at the time of the design, spatial resolution, noise and dynamic range cannot be further optimized. The authors report on a new rad-hard monolithic APS, named DynAMITe (Dynamic range Adjustable for Medical Imaging Technology), developed by the UK MI-3 Plus consortium. This large area detector (12.8 cm × 12.8 cm) is based on the use of two different diode geometries within the same pixel array with different size pixels (50 ¼m and 100 ¼m). Hence the resulting device can possess two inherently different resolutions each with different noise and saturation performance. The small and the large pixel cameras can be reset at different voltages, resulting in different depletion widths. The larger depletion width for the small pixels allows the initial generated photo-charge to be promptly collected, which ensures an intrinsically lower noise and higher spatial resolution. After these pixels reach near saturation, the larger pixels start collecting so offering a higher dynamic range whereas the higher noise floor is not important as at higher signal levels performance is governed by the Poisson noise of the incident radiation beam. The overall architecture and detailed characterization of DynAMITe will be presented in this paper.
Wells K, Goswami B, Rahni AA, Jones J, Alnowami M, Lewis EB, Guy M (2009) A flexible approach to motion correction in nuclear medicine, IEEE Nuclear Science Symposium Conference Record pp. 2534-2539
Motion correction of the abdominal-thoracic region is one of the main research challenges in tomographic nuclear medicine imaging. We address this issue with a flexible data-driven method of motion correction. This uses marker-less stereo tracking of the anterior abdominal-chest surface and a 'virtual dissection'-based registration approach, combined within a novel paricle filtering (PF) framework. The key advantage to this data driven approach is that we do not make gross prior assumptions on the configuration of the hidden state of the system, i.e. the configuration of the internal organs during the emission acquisition process. Instead, at some given time instance, we infer the hidden or unobserved internal organ configuration by using Monte Carlo sampling (and then filtering) of various propositions, or 'particles'. Such estimates are calculated using the previous state (of the internal organs) plus some noise or perturbation of the expected transition to the current state or configuration. We then compare estimated representations of the abdominal-chest anterior surface, derived from the particles or propositions, with an observation of the actual surface, derived from a marker-less stereo imaging system. By examining the differences between the estimated particle or proposition surfaces and actual observed surface data, we can infer the current configuration of the internal organs. After an update step, the process is then repeated for subsequent time points in the emission data. This allows the system to flexibly adopt previously unknown configurations of the internal organs, and thus allow for different modes of breathing (e.g. abdominal vs thoracic-based motion) to be represented. Preliminary results are presented based on using the XCAT phantom to demonstrate the PF approach and the 'virtual-dissection' registration process, alongside results of a parameterized anterior surface model derived from human volunteer data. ©2009 IEEE.
Gutierrez DR, Jia B, Chiverton J, Wells K, Partidge M (2007) Partial volume correction for image-generated arterial input functions, IEEE Nuclear Science Symposium Conference Record 4 pp. 2091-2094
We propose a method for Partial Volume correction and intensity recovery that models blood vessels as small cylinders of known diameter. We use a Bayesian classifier that explicitly models the effects of the point spread function on these cylinders. Although the method requires prior knowledge of the cylinder/arterial width, there is no requirement for any registration. A further advantage is that Region Of Interest (ROI) definition can be limited to only a few axial slices, thus minimizing time averaging. Furthermore, ROI selection requires only approximate placement around the target artery, encompassing both artery and background tissue, so that recovered data values are not operator-dependent. We present results for classifier performance on simulated phantom data of hot cylindrical inserts in a warm background with different contrast to noise ratios. © 2006 IEEE.
Ashrani AA, Smith R, Lewis E, Wells K (2013) Extracting respiratory motion from 4D MRI using organ-wise registration, Progress in Biomedical Optics and Imaging - Proceedings of SPIE 8669
Nuclear Medicine (NM) imaging serves as a powerful diagnostic tool for imaging of biochemical and physiological processes in vivo. The degradation in spatial image resolution caused by the often irregular respiratory motion must be corrected to achieve high resolution imaging. In order perform motion correction more accurately, it is proposed that patient motion obtained from 4D MRI can be used to analyse respiratory motion. To extract motion from the dynamic MRI dataset an organ wise intensity based affine registration framework is proposed and evaluated. Comparison of the resultant motion obtained within selected organs is made against an open source free form deformation algorithm. For validation, the correlation of the results of both techniques to a previous study of motion in 20 patients is found. Organwise affine registration correlates very well (r = 0:9) with a previous study (Segars et al., 2007)1 whilst free form deformation shows little correlation (r = 0:3). This increases the confidence of the organ wise affine registration framework being an effective tool to extract motion from dynamic anatomical datasets. © 2013 SPIE.
Tahavori F, Jones J, Elangovan P, Wells K, Alnowami M, Donovan E (2013) Assessment of Microsoft Kinect technology (Kinect for Xbox and Kinect for windows) for patient monitoring during external beam radiotherapy, IEEE Nuclear Science Symposium Conference Record pp. 1-5 IEEE
In external beam radiotherapy, patient misalignment during set-up and motion during treatment may result in lost dose to target tissue and increased dose to normal tissues, reducing therapeutic benefit. The most common method for initial patient setup uses room mounted lasers and surface marks on the skin. We propose to use the Microsoft Kinect which can capture a complete patient skin surface representing a multiplicity of 3D points in a fast reproducible, marker-less manner. Our first experiments quantitatively assess the technical performance of Kinect technology using a planar test object and a precision motion platform to compare the performance of Kinect for Xbox and Kinect for Windows. Further experiments were undertaken to investigate the likely performance of using the Kinect during treatment to detect respiratory motion, both in supine and prone positions. The Windows version of the Kinect produces superior performance of less than 2mm mean error at 80-100 cm distance. © 2013 IEEE.
Elangovan P, Hadjipanteli A, Mackenzie A, Dance D, Young K, Wells K (2016) OPTIMAM Image Simulation Toolbox - Recent Developments and Ongoing Studies, Breast Imaging; 13th International Workshop, IWDM 2016 pp. 668-675
Virtual clinical trials (VCTs) are increasingly being seen as a viable pre-clinical method for evaluation of imaging systems in breast cancer screening. The CR-UK funded OPTIMAM project is aimed at producing modelling tools for use in such VCTs. In the initial phase of the project, modelling tools were produced to simulate 2D-mammography and digital breast tomosynthesis (DBT) imaging systems. This paper elaborates on the new tools that have recently been developed for the current phase of the OPTIMAM project. These new additions to the framework include tools for simulating synthetic breast tissue, spiculated masses and variable-angle DBT systems. These tools are described in the paper along with the preliminary validation results. Four-alternative forced choice (4-AFC) type studies deploying these new tools are underway. The results of the ongoing 4AFC studies investigating minimum detectable contrast/size of masses/microcalcifications for different modalities and system designs are presented.
Diaz O, Elangovan P, Wells K, Enshaeifar S, Veale M, Wilson M, Seller P, Cernik R, Pani S (2014) Breast CT image simulation framework for optimisation of lesion visualisation, IEEE Nuclear Science Symposium Conference Record pp. 1-5 IEEE
Although X-ray mammography is the gold standard technique for breast cancer detection, it suffers from limitations due to tissue superposition which could either obscure or mimic a breast lesion. Dedicated breast computed-tomography (BrCT) represents an alternative technology with the potential to overcome these limitations. However, this technology is still under investigation in order to study and improve certain parameters (e.g. dose, scattered radiation, etc.). In this work, an image simulation framework is proposed to generate realistic BrCT images and spectral imaging analysis is explored to enhance the contrast of breast lesions. Results illustrated an improvement in contrast between 5 and 10% when the final image is reconstructed using X-ray photons with energies between 21 and 30 keV, in comparison with the reconstructed image from the polychromatic energy spectrum recorded within the image receptor. © 2013 IEEE.
Tirunagari Santosh, Poh Norman, Wells Kevin, Bober Miroslaw, Gorden I, Windridge David (2017) Movement correction in DCE-MRI through windowed and reconstruction dynamic mode decomposition, Machine Vision and Applications 28 (3-4) pp. 393-407 Springer Verlag
Images of the kidneys using dynamic contrast-enhanced magnetic resonance renography (DCE-MRR) contains unwanted complex organ motion due to respiration. This gives rise to motion artefacts that hinder the clinical assessment of kidney function. However, due to the rapid change in contrast agent within the DCE-MR image sequence, commonly used intensity-based image registration techniques are likely to fail. While semi-automated approaches involving human experts are a possible alternative, they pose significant drawbacks including inter-observer variability, and the bottleneck introduced through manual inspection of the multiplicity of images produced during a DCE-MRR study. To address this issue, we present a novel automated, registration-free movement correction approach based on windowed and reconstruction variants of dynamic mode decomposition (WR-DMD). Our proposed method is validated on ten different healthy volunteers? kidney DCE-MRI data sets. The results, using block-matching-block evaluation on the image sequence produced by WR-DMD, show the elimination of 99%99% of mean motion magnitude when compared to the original data sets, thereby demonstrating the viability of automatic movement correction using WR-DMD.
Cabello J, Bailey A, Kitchen I, Clark A, Crooks J, Halsall R, Key-Charriere M, Martin S, Prydderch M, Turchetta R, Wells K (2006) Digital Autoradiography using CCD and CMOS Imaging Technology, 2006 IEEE Nuclear Science Symposium Conference Record 4 pp. 2607-2612 Institute of Electrical and Electronics Engineers
CCD and CMOS imaging technologies can be applied to thin tissue Autoradiography as potential imaging alternatives
to using conventional film. In this work, we compare two
particular devices; a CCD operating in slow scan mode and a
CMOS-based Active Pixel sensor, operating at near video rates. Both imaging sensors have been operated at room temperature with images produced from calibrated microscales and radiolabelled tissue samples. We also compare these digital imaging technologies with the use of conventional film. We show first comparative results obtained with 14C calibrated microscales and 35S radiolabelled tissue sections. We also present first results of 3H images produced under direct irradiation of a CCD sensor operating at room temperature. Compared to film, silicon-based imaging technologies exhibit enhanced sensitivity, dynamic range and linearity.
Elangovan Premkumar, Mackenzie Alistair, Dance David R, Young Kenneth C, Wells Kevin (2018) Lesion detectability in 2D-mammography and digital breast tomosynthesis using different targets and observers, Physics in Medicine & Biology 63 (9) 095014 pp. 1-10 IOP Publishing

This work investigates the detection performance of specialist and non-specialist observers for different targets in 2D-mammography and digital breast tomosynthesis (DBT) using the OPTIMAM virtual clinical trials (VCT) Toolbox and a 4-alternative forced choice (4AFC) assessment paradigm.

Using 2D-mammography and DBT images of virtual breast phantoms, we compare the detection limits of simple uniform spherical targets and irregular solid masses. Target diameters of 4 mm and 6 mm have been chosen to represent target sizes close to the minimum detectable size found in breast screening, across a range of controlled contrast levels. The images were viewed by a set of specialist observers (five medical physicists and six experienced clinical readers) and five non-specialists.

Combined results from both observer groups indicate that DBT has a significantly lower detectable threshold contrast than 2D-mammography for small masses (4 mm: 2.1% [DBT] versus 6.9% [2D]; 6 mm: 0.7% [DBT] versus 3.9% [2D]) and spheres (4 mm: 2.9% [DBT] versus 5.3% [2D]; 6 mm: 0.3% [DBT] versus 2.2% [2D]) (p  0.0001). Both observer groups found spheres significantly easier to detect than irregular solid masses for both sizes and modalities (p  0.0001) (except 4 mm DBT). The detection performances of specialist and non-specialist observers were generally found to be comparable, where each group marginally outperformed the other in particular detection tasks. Within the specialist group, the clinical readers performed better than the medical physicists with irregular masses (p  0.0001).

The results indicate that using spherical targets in such studies may produce over-optimistic detection thresholds compared to more complex masses, and that the superiority of DBT for detecting masses over 2D-mammography has been quantified. The results also suggest specialist observers may be supplemented by non-specialist observers (with training) in some types of 4AFC studies.

Gilat Schmidt Taly, Lo Joseph Y., Chen Guang-Hong, Wilkinson Louise, Wallis Matthew G., Given-Wilson Rosalind M., Mihalas E., Dance David R., Wells Kevin, Young Kenneth C., Elangovan P., Alnowami Majdi R., Cooke V. (2018) Design and validation of biologically inspired spiculated breast lesion models utilizing structural tissue distortion, Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 105730B (9 March 2018) Society of Photo-optical Instrumentation Engineers (SPIE)
The use of conventional clinical trials to optimise technology and techniques in breast cancer screening carries with it issues of dose, high cost and delay. This has motivated the development of Virtual Clinical Trials (VCTs) as an alternative in-silico assessment paradigm. However, such an approach requires a set of modelling tools that can realistically represent the key biological and technical components within the imaging chain. The OPTIMAM image simulation toolbox provides a complete validated end-to-end solution for VCTs, wherein commonly-found regular and irregular lesions can be successfully and realistically simulated. As spiculated lesions are the second most common form of solid mass we report on our latest developments to produce realistic spiculated lesion models, with particular application in Alternative Forced Choice trials. We make use of sets of spicules drawn using manually annotated landmarks and interpolated by a fitted 3D spline for each spicule. Once combined with a solid core, these are inserted into 2D and tomosynthesis image segments and blended using a combination of elongation, rotational alignment with background, spicule twisting and core radial contraction effects. A mixture of real and simulated images (86 2D and 86 DBT images) with spiculated lesions were presented to an experienced radiologist in an observer study. The latest observer study results demonstrated that 88.4% of simulated images of lesions in 2D and 67.4% of simulated lesions in DBT were rated as definitely or probably real on a six-point scale. This presents a significant improvement on our previous work which did not employ any background blending algorithms to simulate spiculated lesions in clinical images.
Samuelson Frank W., Nishikawa Robert M., Patel Mishal, Elangovan Prem, Wells Kevin, Halling-Brown Mark D., Awais Muhammad, Dance David R., Young Kenneth, Mills G., Alnowami Majdi (2018) A deep learning model observer for use in alterative forced choice virtual clinical trials, Proc. SPIE 10577, Medical Imaging 2018: Image Perception, Observer Performance, and Technology Assessment Society of Photo-optical Instrumentation Engineers (SPIE)
Virtual clinical trials (VCTs) represent an alternative assessment paradigm that overcomes issues of dose, high cost and delay encountered in conventional clinical trials for breast cancer screening. However, to fully utilize the potential benefits of VCTs requires a machine-based observer that can rapidly and realistically process large numbers of experimental conditions. To address this, a Deep Learning Model Observer (DLMO) was developed and trained to identify lesion targets from normal tissue in small (200 x 200 pixel) image segments, as used in Alternative Forced Choice (AFC) studies. The proposed network consists of 5 convolutional layers with 2x2 kernels and ReLU (Rectified Linear Unit) activations, followed by max pooling with size equal to the size of the final feature maps and three dense layers. The class outputs weights from the final fully connected dense layer are used to consider sets of n images in an n-AFC paradigm to determine the image most likely to contain a target. To examine the DLMO performance on clinical data, a training set of 2814 normal and 2814 biopsy-confirmed malignant mass targets were used. This produced a sensitivity of 0.90 and a specificity of 0.92 when presented with a test data set of 800 previously unseen clinical images. To examine the DLMOs minimum detectable contrast, a second dataset of 630 simulated backgrounds and 630 images with simulated lesion and spherical targets (4mm and 6mm diameter), produced contrast thresholds equivalent to/better than human observer performance for spherical targets, and comparable (12 % difference) for lesion targets.
Edmunds David M., Gothard Lone, Khabra Komel, Kirby Anna, Madhale Poonam, McNair Helen, Roberts David, Tang KK, Symonds-Tayler Richard, Tahavori Fatemeh, Wells Kevin, Donovan Ellen (2018) Low-cost Kinect Version 2 imaging system for breath hold monitoring and gating: Proof of concept study for breast cancer VMAT radiotherapy, Journal of Applied Clinical Medical Physics 19 (3) pp. 71-78 American Association of Physicists in Medicine
Voluntary inspiration breath hold (VIBH) for left breast cancer patients has been shown to be a safe and effective method of reducing radiation dose to the heart. Currently, VIBH protocol compliance is monitored visually. In this work, we establish whether it is possible to gate the delivery of radiation from an Elekta linac using the Microsoft Kinect version 2 (Kinect v2) depth sensor to measure a patient breathing signal. This would allow contactless monitoring during VMAT treatment, as an alternative to equipment?assisted methods such as active breathing control (ABC). Breathing traces were acquired from six left breast radiotherapy patients during VIBH. We developed a gating interface to an Elekta linac, using the depth signal from a Kinect v2 to control radiation delivery to a programmable motion platform following patient breathing patterns. Radiation dose to a moving phantom with gating was verified using point dose measurements and a Delta4 verification phantom. 60 breathing traces were obtained with an acquisition success rate of 100%. Point dose measurements for gated deliveries to a moving phantom agreed to within 0.5% of ungated delivery to a static phantom using both a conventional and VMAT treatment plan. Dose measurements with the verification phantom showed that there was a median dose difference of better than 0.5% and a mean (3% 3 mm) gamma index of 92.6% for gated deliveries when using static phantom data as a reference. It is possible to use a Kinect v2 device to monitor voluntary breath hold protocol compliance in a cohort of left breast radiotherapy patients. Furthermore, it is possible to use the signal from a Kinect v2 to gate an Elekta linac to deliver radiation only during the peak inhale VIBH phase.
PET image degradation imposed by patient respiratory motion is a well-established problem in
clinical oncology; strategies exist to study and correct this. Some attempt to minimise or arrest
patient motion through restraining hardware; their effectiveness is subject to the comfort and compliance.
Another practice is to gate PET data based on signals acquired from an external device.
This thesis presents several contributions to the field of respiratory motion correction research in
PET imaging. First and foremost, this thesis presents a framework which allows a researcher to
process list mode data from a Siemens Biograph mCT scanner and reconstruct sinograms of which
in the open source image reconstruction package STIR. Secondly, it demonstrates the viability of a
depth camera for respiratory monitoring and gating in a clinical environment. It was demonstrated
that it was an effective device to capture anterior surface motion. Similarly, it has been shown
that it can be used to perform respiratory gating. The third contribution is the design, implementation
and validation of a novel respiring phantom. It has individually programmable degrees of
freedom and was able to reproduce realistic respiration motion derived from real volunteers. The
final contribution is a new gating algorithm which optimises the number and width of gates based
on respiratory motion data and the distribution of radioactive counts. This new gating algorithm
iterates on amplitude based gating, where gates as positioned based on respiratory pose at a given
instant. The key improvement is that it considers the distribution of counts as a consequence of
the distribution of motion in a typical PET study. The results show that different studies can be
optimised with a unique number of gates based on the maximum extent of motion present and
can take into account shifts in baseline position due to patient perturbation.
7
Bio-medical imaging is a large umbrella term which covers a number of different imaging modalities used in healthcare today, spanning pre-clinical imaging, to diagnostic imaging and imaging to assist and plan patient treatment. This field of research is pivotal to driving advances in healthcare. This is underpinned by advances in new detector technologies which have the potential to reduce image acquisition time and dose, improving image quality and offer more accurate tools for diagnosis and treatment.

Large area CMOS Active Pixel Sensors (APSs) have the potential to deliver these advances in such demanding and continuously evolving field; large imaging area, together with low noise, low cost, fast readout, high dynamic range and potential for in-pixel intelligence have made this technology an ideal candidate to displace currently used imaging technologies in this field.

This thesis represents the first investigation into the capabilities of large area CMOS APSs to be used across a number of different imaging modalities in bio-medical science, spanning protein imaging to proton Computed Tomography (CT), using both ionising and non-ionising radiation sources. A novel characterisation of the detector performance has been carried out and set into context of commonly used detectors for bio-medical imaging. Considering the performance parameters assessed for this detector, in comparison with digital detectors commonly used in the clinical practise, this demonstrates how such large area sensor technology may be successfully employed in bio-medical imaging.

The novel large area CMOS APS, studied in this work, is proposed as a multi- modality imaging platform for use in pre-clinical science. For the first time direct ?contact print? imaging of radioactive and optical labeled biological samples on a large imaging area has been demonstrated, showing its potential application to a broad range of ionising and non-ionising imaging probes. The protein detection capability of this detector has been compared with both film emulsion and commercially available digital systems, demonstrating a higher resolution in protein detection than either film emulsion or a commonly used commercial CCD-based western blotting detection system. Also, when detection capabilities of this imaging system are compared with the state-of-the art devices for tissue autoradiography, this detector system exhibits a sensitivity comparable to that reported for its competitors, whilst offering the largest imaging area. Both these proof of concepts pave the way for large area CMOS APSs to be used as a multi- modality imaging platform in life science.

The radiation hardness of a novel large area CMOS APS, designed for medical applications and hardened-by-design, is presented. The radiation damage, produced in this sensor by X-ray and proton irradiation, has been studied as function of total ionising dose and displacement damage dose. The damage contributions from ionising and non-ionising energy deposition have been separated for the proton field and proved independent from proton energy providing a further verification of the Non Ionising Energy Loss (NIEL) scaling hypothesis. The lifetime of this detector for routine use in clinical practice has been evaluated as high as 4 years when used in a typical MegaVolt- age radiotherapy environment, demonstrating how such large area sensor technology may be successfully employed in X-ray and proton based imaging applications.

The feasibility of using CMOS APSs as energy-range detectors in proton CT has been demonstrated. Capability of single proton counting, together with potential of energy deposition measurements, have been demonstrated for CMOS APSs. Furthermore, experimental work, based on a simple stack of two CMOS sensors, as well as simulation work has been carried out to prove the capability of such a detection system for pro- ton tracking. Novel algorithms have been developed to perform proton tracking in a CMOS ene

It is estimated that over half of current adults within Great Britain under the age of 65 will be diagnosed with cancer at some point in their lifetime. Medical Imaging forms an essential part of cancer clinical protocols and is able to furnish morphological, metabolic and functional information. The imaging of molecular interactions of biological processes in vivo with Positron Emission Tomography (PET) is informative not only for disease detection but also therapeutic response. The qualitative and quantitative accuracy of imaging is thus vital in the extraction of meaningful and reproducible information from the images, allowing increased sensitivity and specificity in the diagnosis and precision of image guided treatment. Furthermore the utilization of complementary information obtained via Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) in integrated PET-CT and PET-MR devices offers the potential for the synergistic effects of hybrid imaging to provide increased detection and precision of diagnosis with reduced radiation dose in a fully comprehensive single imaging examination. With the increasing sophistication in imaging technology respiratory organ motion during imaging has demonstrated itself to be a major degrading factor of PET image resolution. A modest estimate of respiratory motion amplitude of 5mm, results in PET system resolution degrading from H 5mm to H8.5mm. This evidently has an impact on cancer lesion detectability. Therefore accurate and robust methods for respiratory motion correction are required for both clinical effectiveness and economic justification for purchasing state of the art hybrid PET scanners with high resolution capabilities. In addition the judicious use of imaging resources from hybrid imaging devices coupled with advanced image processing / acquisition protocols will allow optimization of data used for improving quantitative accuracy of PET images and those used for clinical interpretation. In essence it would prove impractical to use the MR scanner purely for monitoring respiratory motion.

Numerous methods exist to attempt to correct PET imaging for respiratory motion. As presented in this thesis many methods demonstrate themselves to be ineffective in the clinical setting where the patients breathing patterns appear irregular in comparison to the idealized situation of regular periodic motion. Advanced respiratory motion correction techniques utilize hybrid PET/CT, PET/MR scanners coupled with an external source of information which serves as a surrogate to build a static correspondence to the estimated internal respiratory motion. Static models however are unable to adapt to their external environment and do not consider time dependent changes in the state of a system. A further confounding factor in the development and assessment of motion correction schemes for medical imaging data is the inability to acquire volumetric data with high contrast and high spatial and temporal resolution which serves as a ground truth for quantifying model accuracy and confidence. This thesis addresses both problems by analysing respiratory motion correspondence modelling under a manifold learning and alignment paradigm which may be used to consolidate many of the respiratory motion estimation models that exist today. A Bayesian approach is adopted in this work to incorporate a-priori information into the model building stage for a more robust, flexible adaptive respiratory motion estimation / correction framework.

This thesis constructs and tests the first proposed adaptive motion model to correlate a surrogate signal with internal motion. This adaptive approach allows the relationship between external surrogate signal and internal motion to change dependent upon breathing pattern and system noise. The adaptive model was compared to a state-of the-art static model and allows more accurate motion estimates to be made when the patient is breathing with an irregular pattern. Testing perfo

Hadjipanteli Andria, Elangovan Premkumar, Mackenzie Alistair, Wells Kevin, Dance David R., Young Kenneth C. (2019) The threshold detectable mass diameter for 2D-mammography and digital breast tomosynthesis, PHYSICA MEDICA 57 pp. 25-32 IST EDITORIALI POLGRAFICI INT
Digital breast tomosynthesis (DBT) is currently under consideration for replacement of, or combined use with
2D-mammography in national breast screening programmes. To investigate the potential benefits that DBT can bring to screening, the threshold detectable lesion diameters were measured for different forms of DBT in comparison to 2D-mammography. The aim of this study was to compare the threshold detectable mass diameters obtained with narrow angle (15°/15 projections) and wide angle (50°/25 projections) DBT in comparison to 2Dmammography.
Simulated images of 60mm thick compressed breasts were produced with and without masses using a set of validated image modelling tools for 2D-mammography and DBT. Image processing and reconstruction were performed using commercial software. A series of 4-alternative forced choice (4AFC) experiments was conducted for signal detection with the masses as targets. The threshold detectable mass diameter was found for each imaging modality with a mean glandular dose of 2.5 mGy. The resulting values of the threshold diameter for 2D-mammography (10.2 ± 1.4 mm) were found to be larger (p
Smith Rhodri L, Rahni Ashrani Aizzudin Abd, Wells Kevin (2018) A Kalman based approach with EM optimization for respiratory motion modelling in medical imaging, IEEE Transactions on Radiation and Plasma Medical Sciences IEEE
Respiratory motion degrades quantitative and qualitative
analysis of medical images. Estimation and hence correction
of motion commonly uses static correspondence models
between an external surrogate signal and internal motion. This work presents a patient specific respiratory motion model with
the ability to adapt in the presence of irregular motion via
a Kalman filter with Expectation Maximisation for parameter
estimation. The adaptive approach introduces generalizability
allowing the model to account for a broader variety of motion.
This may be required in the presence of irregular breathing and
with different sensors monitoring the external surrogate signal.
The motion model framework utilizing an adaptive Kalman filter
approach is tested on dynamic MRI data of nine volunteers and
compared to a state-of-the-art static total least squares approach.
Results demonstrate the framework is capable of reducing motion
to the order of effective in the presence of irregular motion, assessed using the
F test for model comparison. Utilizing the total sum of squares
of estimated vector field error from the calculated ground truth,
we observe approximately a fifty percent reduction in root mean
square error and thirty percent reduction in standard deviation
utilizing the Kalman model (EKF) in comparison to a static
counterpart.
About 1.7 million new cases of breast cancer were estimated by the World Health Organization (WHO) in 2012, accounting for 23 percent of all female cancers. In the UK 33 percent of women aged 50 and above were diagnosed in the same year, thus positioning the UK as the 6th highest in breast cancer amongst the European countries. The national Screening programme in the UK has been focused on the procedure of early detection and to improve prognosis by timely intervention to extend the life span of patients. To this end, the National Health Service Breast Screening Programme (NHSBSP) employs 2-D planar mammography because it is considered to be the gold standard technique for early breast cancer detection worldwide. Breast tomosynthesis has shown great promise as an alternative method for removing the intrinsic overlying clutter seen in conventional 2D imaging. However, preliminary work in breast CT has provided a number of compelling aspects that motivates the work featured in this thesis. These advantages include removal of the need to mechanically compress the breast which is a source of screening non-attendances, and that it provides unique cross sectional images that removes almost all the overlying clutter seen in 2D. This renders lesions more visible and hence aids in early detection of malignancy. However work in Breast CT to date has been focused on using scaled down versions of standard clinical CT systems. By contrast, this thesis proposes using a photon counting approach. The work of this thesis focuses on investigating photoncounting detector technology and comparing it to conventional CT in terms of contrast visualization. Results presented from simulation work developed in this thesis has demonstrated the ability of photoncounting detector technology to utilize data in polychromatic beam where contrast are seen to decrease with increasing photon energy and compared to the conventional CT approach which is the standard clinical CT system.
Diaz Oliver, Elangovan Premkumar, Young Kenneth C., Wells Kevin, Dance David R. (2019) Simple method for computing scattered radiation in breast tomosynthesis, Medical Physics American Association of Physicists in Medicine

Purpose

Virtual clinical trials (VCT) are a powerful imaging tool that can be used to investigate digital breast tomosynthesis (DBT) technology. In this work, a fast and simple method is proposed to estimate the two?dimensional distribution of scattered radiation which is needed when simulating DBT geometries in VCTs.

Methods

Monte Carlo simulations are used to precalculate scatter?to?primary ratio (SPR) for a range of low?resolution homogeneous phantoms. The resulting values can be used to estimate the two?dimensional (2D) distribution of scattered radiation arising from inhomogeneous anthropomorphic phantoms used in VCTs. The method has been validated by comparing the values of the scatter thus obtained against the results of direct Monte Carlo simulation for three different types of inhomogeneous anthropomorphic phantoms.

Results

Differences between the proposed scatter field estimation method and the ground truth data for the OPTIMAM phantom had an average modulus and standard deviation of over the projected breast area of 2.4 ± 0.9% (minimum ?17.0%, maximum 27.7%). The corresponding values for the University of Pennsylvania and Duke University breast phantoms were 1.8 ± 0.1% (minimum ?8.7%, maximum 8.0%) and 5.1 ± 0.1% (minimum ?16.2%, maximum 7.4%), respectively.

Conclusions

The proposed method, which has been validated using three of the most common breast models, is a useful tool for accurately estimating scattered radiation in VCT schemes used to study current designs of DBT system.

Smith Rhodri Lyn, Dasari Paul, Lindsay Clifford, King Michael A, Wells Kevin (2019) Dense motion propagation from sparse samples, Physics in Medicine and Biology IOP Publishing
There are many applications for which sparse, or partial sampling of
dynamic image data can be used for articulating or estimating motion within the
medical imaging area. In this new work, we propose a generalized framework for
dense motion propagation from sparse samples which represents an example of transfer
learning and manifold alignment, allowing the transfer of knowledge across imaging
sources of different domains which exhibit different features. Many such examples
exist in medical imaging, from mapping 2D ultrasound or fluoroscopy to 3D or 4D
data or monitoring dynamic dose delivery from partial imaging data in radiotherapy.
To illustrate this approach we animate, or articulate, a high resolution static MR
image with 4D free breathing respiratory motion derived from low resolution sparse
planar samples of motion. In this work we demonstrate that sparse sampling of
dynamic MRI may be used as a viable approach to successfully build models of freebreathing respiratory motion by constrained articulation. Such models demonstrate
high contrast, and high temporal and spatial resolution that have so far been hitherto
unavailable with conventional imaging methods. The articulation is based on using
a propagation model, in the eigen domain, to estimate complete 4D motion vector
fields from sparsely sampled free-breathing dynamic MRI data. We demonstrate that
this approach can provide equivalent motion vector fields compared to fully sampled
4D dynamic data, whilst preserving the corresponding high resolution / high contrast
inherent in the original static volume. Validation is performed on three 4D MRI
datasets using 8 extracted slices from a fast 4D acquisition (0.7sec per volume). The
estimated deformation fields from sparse sampling are compared to the fully sampled
equivalents, resulting in an rms error of the order of 2mm across the entire image
volume. We also present exemplar 4D high contrast, high resolution articulated
volunteer datasets using this methodology. This approach facilitates greater freedom
in the acquisition of free breathing respiratory motion sequences which may be used to
inform motion modelling methods in a range of imaging modalities and demonstrates
that sparse sampling of free breathing data may be used within a manifold alignment
and transfer learning paradigm to estimate fully sampled motion. The method may also
be applied to other examples of sparse sampling to produce dense motion propagation.

Background: Chiari-like malformation (CM) is a complex malformation of the skull and cranial cervical vertebrae potentially resulting in pain and secondary syringomyelia (SM). CM associated pain can be challenging to diagnose [35]. We propose a machine learning approach to characterize morphological changes in dogs that may/may not be apparent to human observers. This data driven approach can remove potential bias (or blindness) that may be produced by a hypothesis driven expert observer approach.

Hypothesis/Objectives: Using a novel machine learning approach to understand neuromorphological change and to identify image-based biomarkers in dogs with CM associated pain (CM-P) and symptomatic SM (SM-S), with the aim of deepening the understanding on these disorders.
Animals: 32 client owned Cavalier King Charles Spaniels (CKCS) (11 controls, 10 CM-P, 11 SM-S)

Methods: Retrospective study using T2W midsagittal DICOM anonymized images which were mapped to a images of a average clinically normal CKCS reference using Demons image registration. Key deformation features were automatically selected from the resulting deformation maps. A kernelized Support Vector Machine was used for classifying characteristic localized changes in morphology.

Results: Candidate biomarkers were identified with receiver operating characteristic (ROC) curves with area under the curve (AUC) of 0.78 (sensitivity = 82%; specificity = 69%) for the CM-P biomarkers collectively, and an AUC of 0.82 (sensitivity = 93%; specificity = 67%) for the SM biomarkers collectively.

Conclusions and clinical importance:
Machine learning techniques can assist CM/SM diagnosis and understand abnormal morphology location with the potential to be applied to a variety of breeds and conformational diseases.