Detecting and refurbishing ground truth errors during training of deep learning-based echocardiography segmentation models
arXiv:2604.12832v1 Announce Type: cross
Abstract: Deep learning-based medical image segmentation typically relies on ground truth (GT) labels obtained through manual annotation, but these can be prone to random errors or systematic biases. This study …