Dice Semimetric Losses: Optimizing the Dice Score with Soft Labels

arXiv:2303.16296v4 Announce Type: replace-cross
Abstract: The soft Dice loss (SDL) has taken a pivotal role in numerous automated segmentation pipelines in the medical imaging community. Over the last years, some reasons behind its superior functioning have been uncovered and further optimizations have been explored. However, there is currently no implementation that supports its direct utilization in scenarios involving soft labels. Hence, a synergy between the use of SDL and research leveraging the use of soft labels, also in the context …

arxiv cs.ai cs.cv cs.lg dice labels losses type