Prof Reyer Zwiggelaar

Ir (Groningen), PhD (University College London)

Prof Reyer Zwiggelaar

Professor

Head of the Graduate School (Graduate Centre )

Institute Director of Research

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
Tutor
Lecturer
Additional Lecturer

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

Research Groups

Publications

Deep Learning in Mammography and Breast Histology, an Overview and Future TrendsHamidinekoo, A., Denton, E. R. E., Rampun, Y. A., Honnor, K. & Zwiggelaar, R. 2018 In : Medical Image Analysis.47, p. 45-6723 p.
Classification of Micro-calcification in Mammograms using Scalable Linear Fisher Discriminant AnalysisSuhail, Z., Denton, E. R. E. & Zwiggelaar, R. 2018 In : Medical and Biological Engineering and Computing.
Comparison of Image Intensity, Local and Multi-Atlas Priors in Brain Tissue ClassificationWang, L., Labrosse, F. & Zwiggelaar, R. 2017 (Accepted/In press) In : Medical Physics.44, 11, p. 5782-579413 p.
Automated breast ultrasound lesions detection using convolutional neural networksHoon Yap, M., Pons, G., Marti, J., Ganau, S., Sentís, M., Zwiggelaar, R., Davison, A. & Martí, R. 2017 (Accepted/In press) In : IEEE Journal of Biomedical and Health Informatics .
Tree-based modelling for the classification of mammographic benign and malignant micro-calcification clustersSuhail, Z., Denton, E. R. E. & Zwiggelaar, R. 2017 In : Multimedia Tools and Applications.
More publications on the Research Portal