Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentation 来自 Semantic Scholar 喜欢 0 阅读量: 576 作者:C Chen,Q Dou,H Chen,J Qin,PA Heng 摘要: Unsupervised domain adaptation has increasingly gained interest in medical image ...
Wavelet-based spectrum transfer with collaborative learning for unsupervised bidirectional cross-modality domain adaptation on medical image segmentationUnsupervised domain adaptationMedical image segmentationWavelet transformCollaborative learningUnsupervised cross-modality domain adaptation for medical image segmentation ...
(i) We firstly extend the no prior-aware source-free unsupervised domain adaptation method to bidirectional cross-modality medical image segmentation with unpaired CT and MR images. (ii) The proposed source-free unsupervised domain adaptation framework organically combines feature alignment, image alignmen...
Besides, considering modality, multimodal segmen- tation outperforms single modality results, showing that the 5194 relationship learned between the visual domain and the lan- guage domain can truly benefit temporal segmentation. 5.2. Ablation Study Multiple heuristics ...
* CKD-TransBTS: Clinical Knowledge-Driven Hybrid Transformer with Modality-Correlated Cross-Attention for Brain Tumor Segmentation* 链接: arxiv.org/abs/2207.0737* 作者: Jianwei Lin,Jiatai Lin,Cheng Lu,Hao Chen,Huan Lin,Bingchao Zhao,Zhenwei Shi,Bingjiang Qiu,Xipeng Pan,Zeyan Xu,Biao Huang,...
Unsupervised domain adaptation (UDA) for cross-modality medical image segmentation has shown great progress by domain-invariant feature learning or image appearance translation. Feature-level adaptation based methods learn good domain-invariant features
Wavelet-based spectrum transfer with collaborative learning for unsupervised bidirectional cross-modality domain adaptation on medical image segmentation Unsupervised cross-modality domain adaptation for medical image segmentation has made great progress with the development of adversarial learning-based met... ...
Domain adaptationMulti-modalitySegmentationDomain shift happens in cross-domain scenarios commonly because of the wide gaps between different domains: when applying a deep learning model well-trained in one domain to another target domain, the model usually performs poorly. To tackle this problem, ...
Unsupervised bidirectional cross-modality adaptation via deeply synergistic image and feature alignment for medical image segmentation. IEEE Trans. Med. Imaging 2020, 39, 2494–2505. [Google Scholar] [CrossRef] Cheng, J.; Liu, J.; Xu, Y.; Yin, F.; Wong, D.W.K.; Tan, N.M.; Tao, ...
Recently, bidirectional learning was applied to image-to-image translation problems as well. Li et al. [53] learned the image translation model and the segmentation adaptation model alternatively with a bidirectional learning method. Chen et al. [54] presented a bidirectional cross-modality ...