Heart Disease Diagnosis with Deep Learning – Insight Data

A human heart is an astounding machine that is designed to continually function for up to a century without failure. One of the key ways to measure how well your heart is functioning is to compute its ejection fraction: after your heart relaxes at its diastole to fully fill with blood, what percentage does it pump out upon contracting to its systole? The first step of getting at this metric relies on segmenting (delineating the area of) the ventricles from cardiac images. During my time at the Insight AI Program in NYC, I decided to tackle the right ventricle segmentation challenge from the calls for research hosted by the AI Open Network. I managed to achieve state of the art results with over an order of magnitude less parameters; below is a brief account of how.