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pro vyhledávání: '"Stucki, Nico"'
In this work, we propose an efficient algorithm for the calculation of the Betti matching, which can be used as a loss function to train topology aware segmentation networks. Betti matching loss builds on techniques from topological data analysis, sp
Externí odkaz:
http://arxiv.org/abs/2407.04683
Autor:
Berger, Alexander H., Stucki, Nico, Lux, Laurin, Buergin, Vincent, Shit, Suprosanna, Banaszak, Anna, Rueckert, Daniel, Bauer, Ulrich, Paetzold, Johannes C.
Topological accuracy in medical image segmentation is a highly important property for downstream applications such as network analysis and flow modeling in vessels or cell counting. Recently, significant methodological advancements have brought well-
Externí odkaz:
http://arxiv.org/abs/2403.11001
Image segmentation is a largely researched field where neural networks find vast applications in many facets of technology. Some of the most popular approaches to train segmentation networks employ loss functions optimizing pixel-overlap, an objectiv
Externí odkaz:
http://arxiv.org/abs/2211.15272
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