Self-training for cross-centre coronary vessel segmentation in X-ray angiography using pre-contrast frame subtraction
arXiv:2610.40302v1 Announce Type: cross Abstract: Deep learning models for coronary vessel segmentation in X-ray angiography often perform poorly on data from centres that were not represented in training. Apart from differences in equipment, the labels of the largest public dataset (ARCADE) are incomplete, as only the segments defined in the SYNTAX score are annotated. In this study, we evaluated whether self-training with pseudo-labels can improve performance on external data without addition…