In this paper, a novel uncertainty-aware domain alignment framework is proposed to alleviate the general domain shift problem. To the best of our knowledge, the ...

Automatic and accurate segmentation of anatomical structures on medical images is crucial for detecting various potential diseases.

Jun 22, 2021 · However, adversarial learning may impair the alignment of well-aligned samples as it merely aligns the global distributions across domains. To ...

Jun 14, 2024 · In the domain of uncertainty-aware segmentation, researchers ... Uncertainty-aware domain alignment for anatomical structure segmentation.

Class-balanced deep neural network for automatic ventricular structure segmentation ... Uncertainty-aware domain alignment for anatomical structure segmentation.

Domain adaptation-based image segmentation for brain structures, brain tumor, bone features, and other anatomical regions in the head and neck. List of ...

In this paper, we focus on SFDA for semantic segmentation, in which pseudo labeling based target domain self-training is a common solution. However, pseudo ...

Sep 1, 2021 · ” “Bian et al, Uncertainty-aware domain alignment for anatomical structure segmentation, MedIA” “Li et al, Dual-Teacher++: Exploiting Intra ...

Jun 12, 2023 · Current SFDA methods focus on extracting domain knowledge from the source-trained model but neglects the intrinsic structure of the target ...

This paper presents a novel unsupervised domain adaptation framework for cross-modality cardiac segmentation, by explicitly capturing a common cardiac ...