2023/05/14 | Events | Artificial Intelligence
Fifth ARTORG Seminar organized by the Medical Image Analysis (MIA) group with Dr. Yannick Suter, MIA postdoctoral researcher.
Yannick is a Postdoc in the Medical Image Analysis Group at the ARTORG Center. His current projects include the development of automated image analysis methods for patients with brain tumors and leveraging interpretability techniques to improve the performance and robustness of deep neural networks. He has a Ph.D. and Master’s in Biomedical Engineering from the University of Bern.
Glioblastoma is the most frequent and aggressive primary brain tumor in humans. Due to its fast growth and infiltrative nature, Glioblastoma patients only have a median survival of 15 months. The fast disease progression and low overall survival time make close disease monitoring necessary. Currently, a patient’s response to treatment is assessed based on Magnetic Resonance Imaging (MRI), acquired approximately every three months. The current monitoring criteria rely on surrogate tumor size measurements and additional qualitative assessments. With the success of AI (including deep learning and machine learning), we strive to develop a data-driven, computer-assisted approach to monitoring patients. In this talk, I will give an overview of our efforts to assist radiologists in segmenting tumors, develop data-driven imaging biomarkers, make machine learning models more robust, and leverage interpretability techniques of deep neural networks to improve their robustness and performance.