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Semi-supervised ViT knowledge distillation network with style transfer normalization for colorectal liver metastases survival prediction
We use an attention-based approach that weighs the importance of different slide regions in producing the final classification results.
Image-level supervision and self-training for transformer-based cross-modality tumor segmentation
An image-to-image translation strategy between imaging modalities is used to produce annotated pseudo-target volumes and improve generalization to the unannotated target modality.
Comparing 3D deformations between longitudinal daily CBCT acquisitions using CNN for head and neck radiotherapy toxicity prediction
Accuracies of 85. 8% and 75. 3% was found for radionecrosis and hospitalization, respectively, with similar performance as early as after the first week of treatment.
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