Diverse Data Augmentation for Learning Image Segmentation with Cross-Modality Annotations

The dearth of annotated data is a major hurdle in building reliable image segmentation models. Manual annotation of medical images is tedious, time-consuming, and significantly variable across imaging modalities. The need for annotation can be ameliorated by leveraging an annotation-rich source moda...

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Bibliographische Detailangaben
Veröffentlicht in:Med Image Anal
Hauptverfasser: Chen, Xu, Lian, Chunfeng, Wang, Li, Deng, Hannah, Kuang, Tianshu, Fung, Steve H., Gateno, Jaime, Shen, Dinggang, Xia, James J., Yap, Pew-Thian
Format: Artigo
Sprache:Inglês
Veröffentlicht: 2021
Schlagworte:
Article
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC8184609/
https://ncbi.nlm.nih.gov/pubmed/33957558
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.media.2021.102060
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