Causality in
Medical Image Computing

About

This MICCAI 2020 half-day tutorial introduces fundamental concepts of causality and its role in medical imaging. We will illustrate how causal reasoning provides a fresh perspective on important topics including key challenges in image-based predictive modelling such as generalization, data scarcity, confounding, robustness, reliability and responsible reporting. Theoretical concepts will be introduced and related to real-world examples from medical imaging such as image classification for computer-aided diagnosis.

The goal of the tutorial is to raise awareness of the importance of taking causal considerations into account when conducting machine learning research for medical imaging. We hope that this tutorial can provide new inputs to the community and may lay the path to exciting new research directions in medical image computing.