SDiPath Trailblazers in AI Series – Prof Anne Martel

AI in Digital Pathology: Opportunities and Challenges

Abstract: The introduction of scanners that are capable of digitizing microscopic slides at high magnification has led to an explosion of interest in computational pathology in general and deep learning applied to whole slide images (WSIs) in particular. In my lab at Sunnybrook, we are developing AI models that can detect cancer, automatically segment regions of interest, and learn predictive and prognostic models that can be used to guide treatment decisions.

In this talk I will outline some of the unique challenges of working with these extremely large WSIs and discuss some of the approaches that we have developed to overcome the problems of sparse annotations and weak, noisy labels.

Bio: Anne Martel is a Professor in Medical Biophysics at the University of Toronto, a Senior Scientist and Tory Family Chair in Oncology at Sunnybrook Research Institute, and a Faculty Affiliate at the Vector Institute, Toronto. Her research program is focused on medical image and digital pathology analysis, particularly on applications of machine learning for segmentation, diagnosis, and prediction/prognosis. In 2006 she co-founded Pathcore, a software company developing complete workflow solutions for digital pathology.

Dr Martel is an active member of the medical image analysis community and is a fellow of the MICCAI Society which represents engineers and computer scientists working in this field.  She has served as a board member of MICCAI and is currently on the editorial board of the journal Medical Image Analysis.

Zoom link: https://unibe-ch.zoom.us/j/64244437918?pwd=ME0zc1JlTFZZMTQ5UERpZGpXY0xRdz09

Register here: https://docs.google.com/forms/d/e/1FAIpQLSeElhR830Xyf2qrZYgHhdGtO7Yd1bRCZmmBgg2fpZdJ5xUXKA/viewform