Uncertainty-Based Ensemble Learning in CMR Semantic Segmentation

ArXi:2502.09269v3 Announce Type: replace Existing methods derive clinical functional metrics from ventricular semantic segmentation in cardiac cine sequences. While performing well on overall segmentation, they struggle with the end slices. To address this, we extract global uncertainty from segmentation variance and use it in our ensemble learning method, Streaming, for classifier weighting, balancing overall and end-slice performance. We