TEDS-Net: enforcing diffeomorphisms in spatial transformers to guarantee topology preservation in segmentations

TEDS-Net: enforcing diffeomorphisms in spatial transformers to guarantee topology preservation in segmentations

Accurate topology is key when performing meaningful anatomical segmentations, however, it is often overlooked in traditional deep learning methods. In this work we propose TEDS-Net: a novel segmentation method that guarantees accurate topology. Our method is built upon a continuous diffeomorphic fra...

書誌詳細
主要な著者:	Wyburd, MK, Jenkinson, M, Dinsdale, NK, Namburete, AIL
フォーマット:	Conference item
言語:	English
出版事項:	Springer 2021

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