MICCAI 2022 Daily – Tuesday

The ejection fraction is probably the most important metric in the clinical evaluation of cardiac function because it tells the clinician how much blood the heart pumps into the body for every beat. This paper proposes a novel neural network architecture that generates two videos for a given cardiac ultrasound scan, including one modified to change the ejection fraction. “ We want to let the clinician compare the true echocardiogram from the patient and an echocardiogram of the same patient with a different ejection fraction, ” Hadrien tells us. “ Same heart, same person, but different ejection fraction, which doesn’t exist. It’s purely hypothetical, but it lets the clinician see if the patient’s heart is in bad condition, good condition, or too good condition, which can also be bad, by comparing the two results visually. ” Thanos adds: “ In real life, a cardiologist can’t say, what if the patient had a 45% instead of a 40% ejection fraction? With our model, they can. ” 8 DAILY MICCAI Tuesday Poster Presentation D’ARTAGNAN: Counterfactual Video Generation Athanasios “ Thanos ” Vlontzos has just completed his PhD at Imperial College London and recently joined Spotify as a Research Scientist. Hadrien Reynaud is currently studying for his PhD at Imperial. Thanos Vlontzos Hadrien Reynaud Their paper explores a novel causal generative model applied to echocardiograms, and they speak to us about it ahead of their poster session this afternoon.