Anatomically Faithful but Temporally Diffuse: Auditing Attribution for Left-Ventricular Ejection-Fraction Estimation from Echocardiography

תקציר מקורי באנגליתarXiv:2607.13738v2 Announce Type: replace-cross Abstract: Deep video models estimate left-ventricular ejection fraction (EF) from echocardiography with near-expert accuracy, and post-hoc attribution is increasingly used to certify that such models look at the right place. Because EF is defined by the end-systolic (ES) and end-diastolic (ED) frames, a faithful explanation must localize not only the left ventricle in space but also the decisive frames in time. We audit attribution faithfulness along three axes -- spatial grounding, perturbation, and temporal reliance -- for two architecturally distinct regressors fine-tuned on EchoNet-Dynamic: a self-supervised VideoMAE transformer audited with Chefer relevance propagation, and a Kinetics-pretrained R(2+1)D convolutional network audited with