MICCAI 2022 Daily – Tuesday

12 DAILY MICCAI Tuesday Poster Presentation believable in terms of how the heart would react if the ejection fraction were, for example, 10%. However, a human being cannot handle a 10% ejection fraction, but that’s a completely different story. ” Co-authors of this paper include experts in causality and cardiology who have guided Thanos and Hadrien on this topic. “ When we were brainstorming how to approach the subject, the cardiologist told us that what we were proposing was interesting and novel, ” Hadrien reveals. “ They were keen to see what could be done and where it could be used. It was very encouraging. ” Bernhard Kainz , Reader in the Department of Computing at Imperial and one of the paper’s co-authors, gives us his perspective: “ I’m heavily biased, of course, but this work is novel because it’s the first MICCAI paper that shows how causality research and machine learning can be connected to provide new tools for diagnostic support. Doctors ask, ‘How would a patient’s scan look if clinical parameter X was different?’ We show several theoretical ways to learn and generate such counterfactuals and a practical application for diagnosing cardiac function with ultrasound. ” Thanos and Hadrien are already considering the next steps and are keen to iron out a small flaw they have identified in their approach. “ The causal framework is supposed to have variables which are completely independent of each other, ” Hadrien points out. “ In our case, the factual and something we call the confounder share some information. We’re thinking of ways to change this. It’s challenging and implies changing many things in the model, but that’s one of the flaws. It’s a work in progress for us. ” Could we see the result at MICCAI in Vancouver next year? “ We hope so! ” To learn more about Thanos and Hadrien’s work, you are invited to visit Poster 5: Computational Physiology & Pathology (In Person) today from 14:30-15:30.