Anatomy-Regularized Representation Learning for Cross-Modality Medical Image Segmentation

An increasing number of studies are leveraging unsupervised cross-modality synthesis to mitigate the limited label problem in training medical image segmentation models. They typically transfer ground truth annotations from a label-rich imaging modality to a label-lacking imaging modality, under an...

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Bibliographic Details
Published in:IEEE Trans Med Imaging
Main Authors: Chen, Xu, Lian, Chunfeng, Wang, Li, Deng, Hannah, Kuang, Tianshu, Fung, Steve, Gateno, Jaime, Yap, Pew-Thian, Xia, James J., Shen, Dinggang
Format: Artigo
Language:Inglês
Published: 2020
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Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC8120796/
https://ncbi.nlm.nih.gov/pubmed/32956048
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TMI.2020.3025133
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