Skeleton Recall Loss for Connectivity Conserving and Resource Efficient
Segmentation of Thin Tubular Structures
Skeleton Recall Loss for Connectivity Conserving and Resource Efficient
Segmentation of Thin Tubular Structures
Accurately segmenting thin tubular structures, such as vessels, nerves, roads or concrete cracks, is a crucial task in computer vision. Standard deep learning-based segmentation loss functions, such as Dice or Cross-Entropy, focus on volumetric overlap, often at the expense of preserving structural connectivity or topology. This can lead to segmentation …