Prof Reyer Zwiggelaar

Ir (Groningen), PhD (University College London)

Prof Reyer Zwiggelaar


Department of Computer Science

Head of the Graduate School (Graduate Centre )

Graduate School

Contact Details


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


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.


Module Coordinator

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

Research Groups


Langenfeld, F, Aderinwale, T, Christoffer, C, Shin, WH, Terashi, G, Wang, X, Kihara, D, Benhabiles, H, Hammoudi, K, Cabani, A, Windal, F, Melkemi, M, Otu, E, Zwiggelaar, R, Hunter, D, Liu, Y, Sirugue, L, Nguyen, HNH, Nguyen, TDH, Nguyen-Truong, VT, Le, D, Nguyen, HD, Tran, MT & Montès, M 2022, 'Surface-based protein domains retrieval methods from a SHREC2021 challenge', Journal of Molecular Graphics and Modelling, vol. 111, 108103.
Waqar, M, Zwiggelaar, R & Tiddeman, B 2021, Contact-Free Pulse Signal Extraction from Human Face Videos: A Review and New Optimized Filtering Approach. in PM Rea (ed.), Advances in Experimental Medicine and Biology. 1 edn, vol. 9, Advances in Experimental Medicine and Biology, vol. 1317, Springer Nature, pp. 181-202.
Wang, L, Zheng, Y, Rampun, A & Zwiggelaar, R 2021, Prostate Cancer Detection Using Image-Based Features in Dynamic Contrast Enhanced MRI. in BW Papież, M Yaqub, J Jiao, AI Namburete & JA Noble (eds), Medical Image Understanding and Analysis - 25th Annual Conference, MIUA 2021, Proceedings. vol. 12722, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12722 LNCS, Springer Nature, pp. 43-55, 25th Annual Conference on Medical Image Understanding and Analysis, MIUA 2021, Virtual, Online, 12 Jul 2021.,
Dustler, M, Bakic, P, Ikeda, DM, Lång, K & Zwiggelaar, R 2021, Realism of mammography tissue patches simulated using perlin noise: A forced choice reading study. in H Bosmans, W Zhao & L Yu (eds), Medical Imaging 2021: Physics of Medical Imaging., 115954X, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 11595, SPIE, Medical Imaging 2021: Physics of Medical Imaging, Virtual, Online, United States of America, 15 Feb 2021.
Rampun, A, Jarvis, D, Griffiths, P, Zwiggelaar, R, Scotney, BW & Armitage, P 2021, 'Single-Input Multi-Output U-Net for Automated 2D Foetal Brain Segmentation of MR Images', Journal of Imaging, vol. 7, no. 10, 200.
More publications on the Research Portal