Eindhoven University of Technology
Suzanne Wetstein Eindhoven University of Technology s.c.wetstein@tue.nl

PhD Candidate
E-mail: s.c.wetstein@tue.nl
Phone: +31 40 24 75581
LinkedIn; Google Scholar


Suzanne Wetstein is a PhD-candidate at the Medical Image Analysis Group at Eindhoven University of Technology under supervision of Prof. Josien Pluim and Dr. Mitko Veta. Her research is on deep learning applied to histopathological image analysis.

Suzanne has a BSc in Applied Physics from Delft University of Technology and a BSc in Economics and Business from Erasmus University Rotterdam. She did her MSc at VU University, where she studied Business Analytics. During her MSc she studied at Nanyang Technological University in Singapore for half a year to gain more machine learning knowledge. Suzanne concluded her MSc with an internship at ORTEC Consulting, where she worked on machine learning approaches for natural language processing applied to chatbots.

Her research interests include machine learning (deep learning), pattern recognition and medical image analysis.


Suzanne C. Wetstein, Allison M. Onken, Gabrielle M. Baker, Michael E. Pyle, Josien P. W. Pluim, Rulla M. Tamimi, Yujing J. Heng, Mitko Veta

Detection of acini in histopathology slides: towards automated prediction of breast cancer risk Inproceedings

SPIE Medical Imaging, 2019.

Abstract | Links | BibTeX


Allison M. Onken, Suzanne Wetstein, Michael Pyle, Josien Pluim, Stuart J. Schnitt, Gabrielle M Baker, Laura C. Collins, Rulla Tamimi, Mitko Veta, Yujing Jan Heng

Deep Learning Networks to Segment and Detect Breast Terminal Duct Lobular Units, Acini, and Adipose Tissue: A Step Toward the Automated Analysis of Lobular Involution as a Marker for Breast Cancer Risk Conference

United States and Canadian Academy of Pathology (USCAP), 2019.

Abstract | BibTeX