Prof Reyer Zwiggelaar

Ir (Groningen), PhD (University College London)

Prof Reyer Zwiggelaar

Professor

Department of Computer Science

Head of the Graduate School (Graduate Centre )

Graduate School

Contact Details

Profile

Reyer Zwiggelaar received the Ir. Degree in Applied Physics from the State University Groningen, Groningen, The Netherlands, in 1989, and the Ph.D. Degree in Electronic and Electrical Engineering from the University College London, London, UK, in 1993. He is currently a Professor at the Department of Computer Science, Aberystwyth University, UK. He is the author or co-author of more than 180 conference and journal papers. His current research interests include Medical Image Understanding, especially Focusing on Mammographic and Prostate Data, Pattern Recognition, Statistical Methods, Texture-Based Segmentation, and Feature-Detection Techniques.

Additional Information

Responsibilities

As Head of the Graduate School, Professor Reyer Zwiggelaar is responsible for the provision of postgraduate education within the University as a whole, and also has a coordinating role in relation to the development of policy on postgraduate matters; the provision of facilities for postgraduates; and the monitoring of academic progress of postgraduate students.

Teaching

Module Coordinator
Coordinator
Lecturer
Tutor

Professor of the Department of Computer Science, Aberystwyth University, UK.

Research Groups

Publications

Rahman, R, Reid, C, Kloer, P, Henchie, A, Thomas, A & Zwiggelaar, R 2024, 'A systematic review of literature examining the application of a social model of health and wellbeing', European Journal of Public Health, vol. 34, no. 3, pp. 467-472. 10.1093/eurpub/ckae008
Paudel, B, Zwiggelaar, R & Akanyeti, O 2024, Expert Model Prediction Through Feature Matching. in MH Yap, C Kendrick, A Behera, T Cootes & R Zwiggelaar (eds), Medical Image Understanding and Analysis : 28th Annual Conference, MIUA 2024, Manchester, UK, July 24–26, 2024, Proceedings, Part II. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14860 LNCS, Springer Nature, pp. 256-269, 28th Annual Conference on Medical Image Understanding and Analysis, MIUA 2024, Manchester, United Kingdom of Great Britain and Northern Ireland, 24 Jul 2024. 10.1007/978-3-031-66958-3_19
Thomas, C, Denton, E & Zwiggelaar, R 2024, Exploring the possibility of extracting cancer morphology from deep feature clusters. in ML Giger, HM Whitney, K Drukker & H Li (eds), 17th International Workshop on Breast Imaging, IWBI 2024., 131741X, Proceedings of SPIE - The International Society for Optical Engineering, vol. 13174, SPIE, 17th International Workshop on Breast Imaging, IWBI 2024, Chicago, United States of America, 09 Jun 2024. 10.1117/12.3026882
Li, G & Zwiggelaar, R 2024, 'Feature learning based on connectivity estimation for unbiased mammography mass classification', Computer Vision and Image Understanding, vol. 238, 103884. 10.1016/j.cviu.2023.103884
Li, G & Zwiggelaar, R 2024, Improving the CNNs Performance of Mammography Mass Classification via Binary Mask Knowledge Transfer. in ML Giger, HM Whitney, K Drukker & H Li (eds), 17th International Workshop on Breast Imaging, IWBI 2024., 131741Y, Proceedings of SPIE - The International Society for Optical Engineering, vol. 13174, SPIE, 17th International Workshop on Breast Imaging, IWBI 2024, Chicago, United States of America, 09 Jun 2024. 10.1117/12.3026884
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