A Novel Topology-Preserving Loss Function for Tubular Structure Segmentation
clDice
CVPR 2021
Authors: Suprosanna Shit and Johannes C. Paetzold et al.
@article{shit2020cldice,
title={clDice - a Topology-Preserving Loss Function for Tubular Structure Segmentation},
author={Shit, Suprosanna and Paetzold, Johannes C and Sekuboyina, Anjany and Zhylka, Andrey and Ezhov, Ivan and Unger, Alexander and Pluim, Josien PW and Tetteh, Giles and Menze, Bjoern H},
journal={arXiv preprint arXiv:2003.07311},
year={2020}
}
Abstract
Accurate segmentation of tubular, network-like structures, such as vessels, neurons, or roads, is relevant to many fields of research. For such structures, the topology is their most important characteristic; particularly preserving connectedness: in the case of vascular networks, missing a connected vessel entirely alters the blood-flow dynamics. We introduce a novel similarity measure termed centerlineDice (short clDice), which is calculated on the intersection of the segmentation masks and their