Invited Lecture: Artificial Intelligence and Digital pathology: Dealing with the Annotation Bottleneck

#Medical #imaging #digital #pathology #machine #learning
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This is an IEEE EMBS Vancouver Chapter and Biomedical Imaging & AI joint event.

 

Presenter: Professor Anne Martel, Medical Biophysics, University of Toronto, ON, Canada

 

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, including self-supervision and multiple instance learning. I will also outline some of the challenges in deploying AI algorithms to the clinic.

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  • Date: 20 Jan 2022
  • Time: 07:00 PM UTC to 08:00 PM UTC
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  • Vancouver, British Columbia
  • Canada
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  • https://bmiai.ubc.ca/

  • Co-sponsored by Biomedical Imaging and AI UBC
  • Starts 15 November 2021 08:35 PM UTC
  • Ends 20 January 2022 08:00 PM UTC
  • No Admission Charge

  Speakers

Prof. Anne Martel of University of Toronto, ON, Canada

Topic:

Professor Anne Martel

Biography:

Anne Martel is a Professor in Medical Biophysics at the University of Toronto, a Senior Scientist at Sunnybrook Research Institute, and a Vector Faculty Affiliate. 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 board member of MICCAI and is currently on the editorial board of Medical Image Analysis.

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