Leshan Sun

With only 20 locally labeled cases, an agentic framework for echocardiographic video performs left ventricular segmentation and ejection fraction estimation. It chains a low-rank-adapted video segmentation foundation model, a mask-guided long-axis regression module and a natural-language interface; on a 98-case Mayo Clinic cohort it lowers median ejection fraction error from 5.47% to 4.33% and raises the share of cases within ±10 percentage points from 80.6% to 83.3%. On the public EchoNet-Dynamic set, segmentation Dice is 0.934 and median ejection fraction error is 4.24%.

With only 20 locally labeled cases, an agentic framework for echocardiographic video performs left ventricular segmentation and ejection fraction estimation. It chains a low-rank-adapted video segmentation foundation model, a mask-guided long-axis regression module and a natural-language interface; on a 98-case Mayo Clinic cohort it lowers median ejection fraction error from 5.47% to 4.33% and raises the share of cases within ±10 percentage points from 80.6% to 83.3%. On the public EchoNet-Dynamic set, segmentation Dice is 0.934 and median ejection fraction error is 4.24%.