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The proposed multimodal deep learning framework improves both recurrence prediction and recurrence subtype discrimination over existing models.
Comprehensive magnetic resonance imaging (MRI) analysis in oncology involves multiple interrelated tasks including volumetric segmentation, grading, staging, and malignancy detection. However, most existing deep learning models are task-specific or sequence-specific, lacking the generalizability required for heterogene...
TRIAGE, Tracer-aware Refinement via Interactive Anatomy-Guided sEgmentation, a 3D STU-Net initialized through masked autoencoding pre-training with an asynchronous masking strategy, aiming to learn transferable anatomical and cross-modal representations before task-specific fine-tuning.
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