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.
U-net: Convolutional networks for biomedical image segmentation, in: International Con- ference on Medical Image Computing and Computer-Assisted Inter- vention, Springer
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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.