Tumor-aware augmentation and anisotropic cropping improve CT-to-MRI transfer for rectal cancer segmentation in hierarchical transformers by reducing attention dilution from padding and enhancing feature adaptation.
Self-supervised pre-training of swin transformers for 3d medical image analysis, in: Proceedings of the IEEE/CVFConferenceonComputerVisionandPatternRecognition
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Tumor-aware augmentation with task-guided attention analysis improves rectal cancer segmentation from magnetic resonance images
Tumor-aware augmentation and anisotropic cropping improve CT-to-MRI transfer for rectal cancer segmentation in hierarchical transformers by reducing attention dilution from padding and enhancing feature adaptation.