Biography Simon Andermatt


Simon Andermatt

Center for medical Image Analysis & Navigation (CIAN)
Department of Biomedical Engineering
University of Basel
Gewerbestrasse 14
4123 Allschwil, Switzerland

Office 14.04.007
Tel: +41 61 207 54 16

Short Biography

Simon Andermatt received his B.Sc. degree in Computer Science at the University of Basel. After half a year of work experience as a PHP and Javascript front- and backend developer in a local start up company for large scale web applications, he enrolled in the Masters program for Biomedical Engineering with a focus on bioimaging at the Swiss Federal Institute of Technology in Zürich. After graduation in 2013, a civilian service (Zivildienst) of half a year at the Center for medical Image Analysis and Navigation (CIAN, then known as MIAC) persuaded him to further delve into the topic of medical image analysis by signing up to become a PhD candidate. Following the civilian service, a few months of traveling to the other side of the world made him realize, there's just no place like Switzerland. He hence came back to commence his work as a PhD candidate at CIAN.

While the main topic of his PhD studies is the automated segmentation of brain lesions in multiple sclerosis, he is interested in all possible applications of advanced machine learning and artificial intelligence in medicine. Current research interests include generative models, loosely-supervised pathology learning, landmark localization and tracking as well as automated 2d to 3d reconstruction using deep learning.


  • Andermatt, S., Papadopoulou, A., Radue, E.-W., Sprenger, T., Cattin, P.: Tracking the Evolution of Cerebral Gadolinium-Enhancing Lesions to Persistent T1 Black Holes in Multiple Sclerosis: Validation of a Semiautomated Pipeline. Journal of Neuroimaging. (2017). (in press)
  • Andermatt, S., Pezold, S., Cattin, P.: Multi-dimensional Gated Recurrent Units for the Segmentation of Biomedical 3D-Data. In: Carneiro, G., Mateus, D., Peter, L., Bradley, A., Tavares, J.M.R.S., Belagiannis, V., Papa, J.P., Nascimento, J.C., Loog, M., Lu, Z., Cardoso, J.S., and Cornebise, J. (eds.) Deep Learning and Data Labeling for Medical Applications. pp. 142–151. Springer International Publishing (2016).