Tumor-aware augmentation and anisotropic cropping mitigate token inefficiency and feature adaptation issues in CT-to-MRI transfer for rectal cancer segmentation, achieving 88.7-91.1% detection rates.
Prospective validation of a low rectal cancer magnetic resonance imaging staging system and development of a local recurrence risk stratification model: the mercury ii study
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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 mitigate token inefficiency and feature adaptation issues in CT-to-MRI transfer for rectal cancer segmentation, achieving 88.7-91.1% detection rates.