May 13, 2022 · We propose Contrastive Domain Disentangle (CDD) network for generalizable medical image segmentation. We first introduce a disentangle network to decompose ...
We propose an efficient framework called Contrastive Domain Disentanglement and Style Augmentation (CDDSA) for generalizable medical image segmentation.
We propose an efficient framework called Contrastive Domain Disentanglement and Style Augmentation (CDDSA) for generalizable medical image segmentation.
Nov 22, 2022 · We propose an efficient Contrastive Domain Disentanglement and Style Augmentation (CDDSA) framework for generalizable medical image segmentation.
This work proposes Contrastive Domain Disentangle (CDD) network, a disentangle network to decompose medical images into an anatomical representation factor ...
CDDSA: Contrastive domain disentanglement and style augmentation for generalizable medical image segmentation. Ran Gu, Guotai Wang, Jiangshan Lu, ...
To tackle this deficiency, we propose Contrastive Domain Disentangle (CDD) network for generalizable medical image segmentation. Disentanglement · Domain ...
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May 13, 2022 · Experimental results on multi-site fundus image datasets for optic cup and disc segmentation show that the CDD has good model generalization.
CDDSA: Contrastive Domain Disentanglement and Style Augmentation for Generalizable Medical Image Segmentation. alphaXiv. There ...
This method introduce a disentangle network to decompose medical images into an anatomical representation and a modality representation, and a style contrastive ...