Cedars-Sinai Medical Center (Smidt Heart Institute) / Ouyang Lab
Fully automated pipeline that scans a complete transthoracic echocardiogram study, identifies the apical-4-chamber color-Doppler clips showing the mitral valve, and grades mitral regurgitation severity at the study level. Combines a view/valve-presence classifier with a spatiotemporal CNN for severity classification. Trained on a private Cedars-Sinai cohort of 58,614 studies and externally validated on 915 studies from Stanford Healthcare.
Architecture
Hybrid
Two-headed view/mitral-valve-presence classifier + spatiotemporal CNN classifier for MR severity on color-Doppler A4C clips, aggregated to study level
Framework
PyTorch
Added to catalog
2026-07-10
Research use only
License for model weights only. Associated code may be licensed seperately, check code source for specific terms.
Cedars-Sinai TTE Color-Doppler Corpus (EchoNet-MR)
58,614 TTE studies with color-Doppler (private); count is studies, not confirmed unique subjects
Severe mitral regurgitation detection
Multi-class classification