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
Additional Lecturer
Blackboard Dept Admin
Tutor

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

Research Groups

Publications

Hamidinekoo, A, Denton, E, Honnor, K & Zwiggelaar, R 2020, An AI-based method to retrieve hematoxylin and eosin breast histology images using mammograms. in H Bosmans, N Marshall & C Van Ongeval (eds), 15th International Workshop on Breast Imaging, IWBI 2020., 1151319, Proceedings of SPIE - The International Society for Optical Engineering, vol. 11513, SPIE, 15th International Workshop on Breast Imaging, IWBI 2020, Leuven, Belgium, 25 May 2020. https://doi.org/10.1117/12.2564298
Hoon Yap, M, Goyal, M, Osman, F, Marti, R, Denton, ERE, Juette, A & Zwiggelaar, R 2020, 'Breast Ultrasound Region of Interest Detection and Lesion Localisation', Artificial Intelligence in Medicine, vol. 107, 101880. https://doi.org/10.1016/j.artmed.2020.101880
Hamidinekoo, A, Garzon Martinez, GA, Ghahremani Boozandani, M, Corke, F, Zwiggelaar, R, Doonan, J & Lu, C 2020, 'DeepPod: A convolutional neural network based quantification of fruit number in Arabidopsis', GigaScience, vol. 9, no. 3, pp. 1-13. https://doi.org/10.1093/gigascience/giaa012
Qu, Y, Fu, Q, Shang, C, Deng, A, Zwiggelaar, R, George, M & Shen, Q 2020, 'Fuzzy-rough assisted refinement of image processing procedure for mammographic risk assessment', Applied Soft Computing, vol. 91, 106230. https://doi.org/10.1016/j.asoc.2020.106230
Suhail, Z & Zwiggelaar, R 2020, Histogram-based approach for mass segmentation in mammograms. in H Bosmans, N Marshall & C Van Ongeval (eds), 15th International Workshop on Breast Imaging, IWBI 2020., 1151325, Proceedings of SPIE - The International Society for Optical Engineering, vol. 11513, SPIE, 15th International Workshop on Breast Imaging, IWBI 2020, Leuven, Belgium, 25 May 2020. https://doi.org/10.1117/12.2563621
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