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MUST-PET achieves superior lesion segmentation and reconstruction accuracy, even with limited labeled data, by harnessing the power of multimodal self-supervised learning across diverse PET-CT scans.
Achieving fully-labeled model performance with 70% less annotation effort could revolutionize automated cancer detection in PET/CT imaging.
