Aug 18, 2022 · We propose Contrastive Semi-supervised learning for Cross Anatomy Domain Adaptation (CS-CADA) that adapts a model to segment similar structures in a target ...

In this work, we design a novel contrastive learning strategy for cross-anatomy domain adaptation, which encourages the model to extract comprehensive domain- ...

Leveraging existing annotated datasets with similar anatomical structures to assist training has a potential for improving the model's performance. However, it ...

Dec 29, 2022 · In this work, we design a novel contrastive learning strat- egy for cross-anatomy domain adaptation, which encourages the model to extract ...

Aug 18, 2022 · Leveraging existing annotated datasets with similar anatomical structures to assist training has a potential for improving the model's ...

For easy evaluation and fair comparison, we are trying to build a semi-supervised medical image segmentation benchmark to boost the semi-supervised learning ...

... Contrastive semi-supervised learning for domain adaptive segmentation across similar anatomical structures. IEEE Transactions on Medical Imaging 42(1), 245 ...

Oct 8, 2023 · Contrastive semi-supervised learning for domain adaptive segmentation across similar anatomical structures IEEE Trans. Med. Imaging 2022 42 ...

Contrastive Semi-supervised Learning for Domain Adaptive Segmentation Across Similar Anatomical Structures ... Semi-supervised learning for Cross Anatomy ...

Missing: Structures. | Show results with:Structures.