Dr Hongying (Lilian) Tang

Senior Lecturer

Qualifications: BEng, MEng, PhD (Cantab)

Email:
Phone: Work: 01483 68 6054
Room no: 10 BB 02

Office hours

Thursday 12:00 - 14:00

Further information

Research Interests

Computer vision, Image processing, Machine learning, Natural language processing

 

Research Collaborations

Moorfields Eye Hospital, Royal Surrey County Hospital, Royal Botanic Gardens, Kew, St Thomas' Hospital, Frimley Health NHS Foundation Trust

 

Publications

Here are a selection of publications:

  • Ann Sofia Skou Thomsen, Phillip Smith, Yousif Subhi, Morten la Cour, Lilian Tang, George M. Saleh, Lars Konge, High correlation between performance on a virtual-reality simulator and real-life cataract surgery, Accepted for publication in Acta Ophthalmologica.
  • Nizar Din, Phil Smith, Krisztina Emeriewen, Anant Sharma, Simon Jones, Hongying Tang, Paul Sullivan, Silvestro Caputo and George M. Saleh, Man vs Machine: Software training for surgeons -an objective evaluation of human and computer-based training tools for cataract surgical performance." Accepted for publication in Journal of Ophthalmology.
  • George M. Saleh, James Wawrzynski, Silvestro Caputo, Tunde Peto, Lutfiah Al turk, Su Wang, Yin Hu, L. Da Cruz, Phil Smith and Hongying Tang, An automated detection system for microaneurysms that is effective across different racial groups, accepted for publication in Journal of Ophthalmology.
  • Wang, Su; Tang, H Lilian; Al turk, Lutfiah; Hu, Yin; Sanei, Saeid; Saleh, George; Peto, Tunde, Localising Microaneurysms in Fundus Images Through Singular Spectrum Analysis, IEEE Transactions on Biomedical Engineering, Print ISSN: 0018-9294, Online ISSN: 1558-2531, Digital Object Identifier: 10.1109/TBME.2016.2585344
  • Hanan S. Alghamdi, Hongying Lilian Tang, Saad A. Waheeb, and Tunde Peto, Automatic Optic Disc Abnormality Detection in Fundus Images: A Deep Learning Approach, 3rd MICCAI workshop on Ophthalmic Medical Image Analysis.
  • Safaei A, Tang HL, Sanei S (2016), Real Time Search Free Multiple License Plate Recognition via Likelihood Estimation of Saliency, accepted for Computers and Electrical Engineering
  •  Safaei A, Tang HL, Sanei S, Incorporating Negentropy in Saliency-based Search Free Car Number Plate Localization, 2016 International Conference on Digital Signal Processing (DSP) 
  • Safaei A, Tang HL, Sanei S (2016) Robust Search-Free Car Number Plate Localization Incorporating Hierarchical Saliency. Journal of Computer Science & Systems Biology, 9:093-103. doi:10.4172/jcsb.1000225
  • James R Wawrzynski, Phillip Smith, Lilian Tang, Tim Hoare, Silvestro Caputo, John Marshall, Michael Tsatsos, George M Saleh, Tracking camera control in endoscopic dacryocystorhinostomy surgery., Clinical Otolaryngology, 2015 Apr 8.  [Epub ahead of print], (ISI Journal Citation Reports © Ranking: 2013: 7/44 (Otorhinolaryngology), Online ISSN: 1749-4486), PMID: 25858299
  • Vassileios Balntas, Edward Johns, Lilian Tang, Krystian Mikolajczyk, PN-Net: Conjoined Triple Deep Network for Learning Local Image Descriptors, arXiv:1601.05030 [cs.CV].
  • H Alghmdi, H Lilian Tang, M Hansen, A O'Shea, L Al turk, T Peto, Measurement of Optical Cup to Disk Ration in Fundus Images for Glaucoma screening, International Workshop on Computational Intelligence for Multimedia Understanding IWCIM 2015, Prague, Czech Republic.
  • T. Peto, G.M. Saleh, Silvestro Caputo, Lutfiah Ismail Al turk, Su Wang, Yin Hu, Hongying Lilian Tang, The Application of Machine Learning to the Automated Detection of Microaneurysms in Different Ethnic Group with Diabetic Retinopathy, European Journal of Ophthalmology.
  • Vassileios Balntas, Lilian Tang, Krystian Mikolajczyk, “BOLD - Binary Online Learnt Descriptor for efficient image matching”, CVPR2015, June 7-12 2015, Boston, Massachusetts.
  • Alghamdi H. S. Tang L, Jin Y, Ensemble Learning Optimization for Diabetic Retinopathy Image Analysis, 10th International Conference on Computer Vision Theory and Applications, 11-14 March 2015, Berlin, Germany.
  • Vassileios Balntas, Lilian Tang, Krystian Mikolajczyk, Improving object tracking with voting from false positive detections, 22nd International Conference on Pattern Recognition, 24-28 August 2014 Stockholm, Sweden.
  • Safaei A, Tang HL. and Sanei S, Search-free license plate localisation based on Saliency and local variance estimation. The 7th International Conference on Machine Vision (ICMV 2014).
  • Tang HL, Goh J, Peto T, Ling BW-K, Al turk L, et al. (2013) The Reading of Components of Diabetic Retinopathy: An Evolutionary Approach for Filtering Normal Digital Fundus Imaging in Screening and Population Based Studies. PLoS ONE 8(7): e66730. doi:10.1371/journal.pone.0066730
  • Smith P, Tang L, Balntas V, Young K, Athanasiadis Y, Sullivan P, Hussain B and Saleh GM, “PhacoTracking” An Evolving Paradigm in Ophthalmic Surgical Training, JAMA Ophthalmol. 2013;131(5):659-661. doi:10.1001/jamaophthalmol.2013.28.
  • Corney DPA, Tang HL, Clark JY, Hu Y, Jin J (2012) Automating Digital Leaf Measurement: The Tooth, the Whole Tooth, and Nothing but the Tooth. PloS ONE 7(8): e42112. doi:10.1371/journal.pone.0042112
  • Clark J, Corney D and Tang L (2012), Automated Plant Identification using Artificial Neural Networks, the 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, May 9-12, 2012 San Diego, California.
  • Hanan Alghamdi and Lilian Tang, Hybrid ACO and TOFA Feature Selection Approach for Text Classification, the 2012 IEEE Congress on Evolutionary Computation, 11-15 June 2012, Brisbane, Australia.
  • S. R. Subramaniam, A. Georgakis, B.W.K.Ling, J.Goh, H.L.Tang, T.Peto and G.Saleh, Optimal and Simultaneous Designs of Hermitian Transforms and Masks for Reducing Intraclass Separations of Feature Vectors for Anomaly Detection of Diabetic Retinopathy Images, IEEE, IET 8th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP 2012), 18-20 July 2012, Poznan, Poland.
  • Jonathan Goh, Lilian Tang, Tunde Peto and George Saleh, An Evolutionary Approach for Determining Hidden Markov Model for Medical Image Analysis, the 2012 IEEE Congress on Evolutionary Computation, 11-15 June 2012, Brisbane, Australia.
  • Corney DPA, Clark JY, Tang HL, Wilkin P, Automatic Extraction of Leaf Characters from Herbarium Specimens, TAXON 61 (1), February 2012: 231–244.
  • Tang, H. L., Peto, T., Goh, J., Jin, Y., & Chuluunkhuu, C. (2011, May). Filtering Normal Diabetic Retinopathy Images Through Evolutionary Computation. European Journal of Ophthalmology, 21(3), 347-348.
  • Baldas, V., Tang, L., Bountris, P., Saleh, G., & Koutsouris, D. (2010). A real-time automatic instrument tracking system on cataract surgery videos for dexterity assessment. Proceedings of the IEEE/EMBS Region 8 International Conference on Information Technology Applications in Biomedicine, ITAB.
  • Goh, J., Tang, L., Al Turk, L., & Jin, Y. (2011). Combining particle swarm optimisation with genetic algorithm for contextual analysis of medical images. HEALTHINF 2011 - Proceedings of the 4th International Conference on Health Informatics, 235-241.
  • Goh, J., Tang, L., & Al Turk, L. (2010). Evolving the structure of hidden Markov models for micro aneurysms detection. 2010 UK Workshop on Computational Intelligence, UKCI 2010.
  • Goh, J., Tang, L., Al Turk, L., Vrikki, C., & Saleh, G. (2010). Detection of micro aneurysms using multiple classifiers and hidden Markov models. HEALTHINF 2010 - 3rd International Conference on Health Informatics, Proceedings, 269-274.
  • Goh, J., Tang, L., Saleh, G., Al Turk, L., Fu, Y., & Browne, A. (2009). Filtering Normal Retinal Images for Diabetic Retinopathy Screening Using Multiple Classifiers. In 2009 9th IEEE International Conference on Information Technology and Applications in Biomedicine, (pp. 609-612). Larnaka, CYPRUS: IEEE.
  • Ho, A. T. S., Zhu, X., & Tang, L. H. (2007). Digital watermarking authentication and restoration for Chinese calligraphy images. In S. Sanei, J. A. Chambers, J. McWhirter, Y. Hicks, & A. G. Constantinides (Eds.), Proceedings of the 2007 15th International Conference on Digital Signal Processing (pp. 483-486). Cardiff Univ, Cardiff, WALES: IEEE.
  • Cheng, X. Q., Tan, S. B., & Tang, L. (2006, July). Using DragPushing to refine concept index for text categorization. Journal of Computer Science and Technology, Springer Boston, Volume 21, Number 4 / July, 2006, pp. 592-596.
  • Chen, L., Tang, H. L., & Wells, I. (2005). Clinical content detection for medical image retrieval. In 2005 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vols 1-7 (pp. 6441-6444). Shanghai, PEOPLES R CHINA: IEEE.
  • Chen L, Tang H L, Wells I, “Determining Clinical Context in a Large-Scale Histological Image Database”, Medical Image Understanding and Analysis 2005, Bristol, 19-20 July 2005.
  • Tang H L, Chen L, “Organ Origin Identification Based on Fine Feature Analysis Using Support Vector Machines”, International Journal of The Computer, The Internet and Management (IJCIM), Vol. 12, No.3, pp.22-31, (September-December, 2004).
  • Chen, L., & Tang, H. L. (2004, February 19). Improved computation of beliefs based on confusion matrix for combining multiple classifiers. IEE Electronics Letters, 40(4), 238-239. doi:10.1049/el:20040176.
  • Tang, H. L., Hanka, R., & Ip, H. H. S. (2003, March). Histological image retrieval based on semantic content analysis. IEEE Transactions On Information Technology In Biomedicine, 7(1), 26-36. doi:10.1109/TITB.2003.808500, MARCH 2003.
  • Chen L, Tang H L, “Dynamic Knowledge Base Updating through Learning from Feedback for Semantic Analysis of Images”, Proceedings of the Third IASTED International Conference on Visualization, Imaging, and Image Processing, September 8-10, 2003, Benalmádena Spain, ISBN: 0-66986-382-2, pp. 522-527.
  • Tang, H. L., & Chen, L. (2003). Improving automatic annotation for medical images based on feedback. In S. H. Chen, H. D. Cheng, D. K. Y. Chiu, S. Das, R. Duro, E. E. Kerre, . J. Wu (Eds.), Proceedings of the 7th Joint Conference on Information Science (pp. 1303-1306). RES TRIANGLE PK, NC: ASSOC INTELLIGENT MACHINERY.
  • Zhao, T., Tang, L. H., Ip, H. H. S., & Qi, F. (2003). On relevance feedback and similarity measure for image retrieval with synergetic neural nets. Neurocomputing, 51, 105-124.
  • Tang L H, Chen L, “IAnnotation - Medical Image Annotation System Based on Relevance Feedback” Proceedings of the International Conference on Intelligent Information Technology, ICIIT-02, Sept 22-25, 2002, pp 215-220, Beijing, China, sponsored by Chinese Computer Federation and in cooperation with IEEE Computer Society.
  • Tang L H, “Computerised Analysis of Aortic Distensibility on Computed Tomography Using a Temporal Active Contour Model”, Int. J. Healthcare Technology and Management, Vol. 4, No. 6, 2002, 433-450.
  • Tang, L. H., Hanka, R., Ip, H. H. S., Cheung, K. K. T., & Lam, R. (2001). An intelligent system for integrating semantic and iconic features for image retrieval. Proceedings of Computer Graphics International Conference, CGI, 240-246.
  • Zhao, T., Tang, L. H., Ip, H. H. S., & Qi, F. (2001). Visual keyword image retrieval based on synergetic neural network for web-based image search. Real-Time Systems, 21(1-2), 127-142.
  • Lam, R. W. K., Ip, H. H. S., Cheung, K. K. T., Tang, L. H. Y., & Hanka, R. (2000). A multi-window approach to classify histological features. Proceedings - International Conference on Pattern Recognition, ICPR 2000, 15(2), 259-262.
  • Tang, L. H. Y., Hanka, R., Ip, H. H. S., Cheung, K. K. T., & Lam, R. (2000). Integration of intelligent engines for a large scale medical image database. Proceedings of the IEEE Symposium on Computer-Based Medical Systems, 235-240.
  • Tang, L. H. Y., Hanka, R., Ip, H. H. S., Cheung, K. K. T., & Lam, R. (2000). Semantic query processing and annotation generation for content-based retrieval of histological images. Proceedings of SPIE - The International Society for Optical Engineering, 3980, 366-375. (Cum Laude Award).
  • Lam, R. W. K., Ip, H. H. S., Cheung, K. K. T., Tang, L. H. Y., & Hanka, R. (2000). Similarity measures for histological image retrieval. Proceedings - International Conference on Pattern Recognition, ICPR 2000, 15(2), 295-298.
  • Lam, R. W. K., Cheung, K. K. T., Ip, H. H. S., Tang, L. H. Y., & Hanka, R. (2000). An iconic and semantic content based retrieval system for histological images. In R. Laurini (Ed.), Advanced in Visual Information Systems, PROCEEDINGS Vol. 1929 (pp. 384-395). LYON, FRANCE: SPRINGER-VERLAG BERLIN.
  • Cheung, K. K. T., Lam, R. W. K., Ip, H. H. S., Tang, L. H. Y., & Hanka, R. (2000). A software framework for combining iconic and semantic content for retrieval of histological images. In R. Laurini (Ed.), Advanced in Visual Information Systems, PROCEEDINGS Vol. 1929 (pp. 488-499). LYON, FRANCE: SPRINGER-VERLAG BERLIN.
  • Tang, L. H. Y., Hanka, R., & Ip, H. H. S. (1999). A review of intelligent content-based indexing and browsing of medical images. Health Informatics Journal, 5(1), 40-49.
  • Cheung K, Ip H, Hanka R., Tang L H, Fuller G, “An Object-oriented Framework for Content-based Image Retrieval Using a 5-tier Architecture”, Proceedings of Asia Pacific Software Engineering Conference 99, pp. 174-177, Takamatsu, Japan, 7-10 Dec. 1999.
  • Tang L H, Hanka R, Lam R., Fuller G., Cheung K, Ip H, “Automatic Semantic Analysis for Histological Images”, Medical Imaging Understanding and Analysis 99 (MIUA'99), Oxford, 19-20 July 1999.
  • Tang, L. H., Hanka, R., Ip, H. H. S., & Lam, R. (1999). Extraction of semantic features of histological images for content-based retrieval of images. In G. J. Blaine, & S. C. Horii (Eds.), MEDICAL IMAGING 1999 - PACS DESIGN AND EVALUATION: ENGINEERING AND CLINICAL ISSUES Vol. 3662 (pp. 360-368). SAN DIEGO, CA: SPIE-INT SOC OPTICAL ENGINEERING.  
  • Tang, L. H., Hanka, R., & Ip, H. H. S. (1998). A system architecture for integrating semantic and iconic content for intelligent browsing of medical images. Proceedings of SPIE - The International Society for Optical Engineering, 3339, 572-580. (Honorable mention Award).

 

I have previously published about 17 papers on natural language processing and machine translation. Here are a few examples:

  • Tang H, Natural Language Understanding, (book), Chapter 12-13, Tsinghua University Press, 1996.
  • Tang et al., “A Lexical Semantics Driven Algorithm Based on Collocation Dictionary”, Chinese Journal of Advanced Software Research, Vol.2, No.3, pp. 287-296 (overseas edition), 1995.
  • Tang et al., “Chinese Sentence Pattern”, Journal of Chinese Information Processing, Vol.7, No.1, pp. 1-6, 1993.

Teaching

COM2028 Introduction to AI

COM3024 Collective Intelligence

Departmental Duties

Year 3 Coordinator (FHEQ Level 6)

Research Projects

  • Morphometric Herbarium Image Data Analysis (MORPHIDAS)  (http://www.computing.surrey.ac.uk/morphidas/)
    • The work, collaborating with Royal Botanic Gardens, Kew, is funded by a 3-year grant, kindly awarded by the Leverhulme Trust.
  • Diabetic Retinopathy Filtering of Normal Images (DAPHNE)
    • This project is in collaboration with Moorfields Eye Hospital, funded by EPSRC (Engineering and Physical Sciences Research Council), to develop an automated system to separate normal and abnormal cases of digital retinal images.
  • Surgical Skill Assessment Through Instrument Motion Analysis (SENTIMENT)
    • This work is in collaboration with Moorfields Eye Hospital, funded by EPSRC (Engineering and Physical Sciences Research Council), to develop an automated system to measure surgeon’s dexterity during an operation procedure.
  • Investigation of stochastic variations in growth rate as the mechanism of drug tolerance in Mycobacterium Tuberculosis
    • funded by BBSRC (Biotechnology and Biological Sciences Research Council). 
    • This is a collaborative 3 year project working with Microbial Science Department. More details on this project and our finding will follow. 
  • Statistical Modelling for Diabetic Retinopathy Detection
    • Funded by King Abdulaziz City for Science and Technology & Ministry of Economy and Planning, Kingdom of Saudi Arabia.
  • Minimal access surgical training, enhancement and reporting software (MASTERS)
    • funded by EPSRC

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