Corpus ID: 236447740

A persistent homology-based topological loss for CNN-based multi-class segmentation of CMR

@article{Byrne2021APH,
  title={A persistent homology-based topological loss for CNN-based multi-class segmentation of CMR},
  author={Nicholas Byrne and James R. Clough and Isra Valverde and G. Montana and Andrew P. King},
  journal={ArXiv},
  year={2021},
  volume={abs/2107.12689}
}
Multi-class segmentation of cardiac magnetic resonance (CMR) images seeks a separation of data into anatomical components with known structure and configuration. The most popular CNN-based methods are optimised using pixel wise loss functions, ignorant of the spatially extended features that characterise anatomy. Therefore, whilst sharing a high spatial overlap with the ground truth, inferred CNN-based segmentations can lack coherence, including spurious connected components, holes and voids… Expand

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