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Video-level labels alone can reliably drive clinical video segmentation: coarse 3D-CAM cues paired with MedSAM2 achieve 94.5% recall and double small-polyp localization without a single manual frame annotation.
MMA-Former's innovative attention mechanism enables spatially adaptive feature extraction, significantly improving PNI prediction accuracy from 3D MRI scans.
LoSA-Net outperforms existing models in predicting perineural invasion by effectively preserving crucial boundary details in 3D MRI scans.
Adaptive routing in transformer-based models can drastically enhance the efficiency of PNI prediction while maintaining high accuracy in capturing subtle imaging features.
