A methodology for breast density measurement using hyperspectral X-ray imaging

This multidisciplinary project, funded by the STFC Cancer Diagnosis Network+, is a collaboration between the University of Surrey, the Detector Development Group at Rutherford Appleton laboratories and the Institute for Cancer Research. It is aimed at developing a method for measurement of breast density by combining cutting-edge technology and image processing algorithms.

Start date
1 October 2020
Duration
3.5 years
Application deadline
Funding information

The studentship fully covers all academic fees with an initial stipend of £15,009 per annum for UK/EU students.

Funding for future years will be subjected to the UKRI increase.

Funding source
STFC Cancer Detection Network+ (50%); the University of Surrey (50%)
Supervised by

About

Breast density, i.e., the proportion of glandular and fatty tissues in a breast, is a known indicator of breast cancer risk. A reliable method to measure it would allow each woman to be allocated a personalised screening schedule, with high-risk women being screened more often than low-risk women. This would optimise breast screening, its cost, and ensure that women are not unnecessarily exposed to potentially harmful X-ray doses.

The project is aimed at developing a novel methodology for breast density measurement.  It is based on the use of the HEXITEC pixellated spectroscopic X-ray detector technology, providing, for each sensor pixel, a spectrum of the radiation detected; this allows simultaneous acquisitions of multiple images at different X-ray energies.

You will characterise and optimise the detector, and develop algorithms to combine the information at different energies to provide a map of the thicknesses of glandular and fatty tissue across the breast. The algorithms will be initially developed on simulated data, then tested experimentally on custom-developed test objects.

The supervisory team at Surrey includes Dr Pani from the Physics department and Prof Evans from the Centre for Vision, Speech and Signal Processing; they will be joined by Dr Harris, team leader of the Imaging for Radiotherapy group at Institute of Cancer Research and Mr Wilson, head of the Detector Development Group at Rutherford Appleton Laboratories.

In addition to the support offered by the Doctoral College of the University and the GRADnet consortium, there will be opportunities for training and mentoring at the two partner institutions, to gain familiarity with both detector development processes and clinical procedures.

The project is funded through the STFC Cancer Diagnosis Network+, bringing together the academic, clinical and industrial community to address the challenges of cancer diagnosis. The student will present their results at Network+ meetings and national/international conferences.

Related links
STFC Cancer Diagnosis Network+ Radiation and Medical Physics Group Centre for Vision, Speech and Signal Processing (cvssp) UKRI The Institute of Cancer Research

Eligibility criteria

Applicants must have a BSc/Masters in Physics or Electronic Engineering with at least 2.1. The ideal candidate will have sound foundations in programming and  strong experimental skills.

UK Students only.

IELTS requirements: 6.5 or above (or equivalent) with 6.0 in each individual category.

How to apply

Applicants should apply through the PhD course page. Please clearly state the studentship title and supervisor on your applicant. Any enquiries about the studentship should be sent to Dr Silvia Pani.

Interviews will take place in late May.

 

 


Application deadline

Contact details

Silvia Pani
18 BB 03
Telephone: +44 (0)1483 682276
E-mail: S.Pani@surrey.ac.uk

Radiation and Medical Physics

The student will have the opportunity to travel to Rutherford Appleton Laboratories to undertake detector training, and to the Institute of Cancer Research for testing on clinical facilities and to undertake training in various aspects of clinical imaging.

Studentships at Surrey

We have a wide range of studentship opportunities available.