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To address the data scarcity bottleneck in deep learning (DL) dose prediction by establishing a foundation model-based transfer learning framework. We aim to demonstrate that adapting large-scale public priors to institutional da...

Low-count PET acquisition and inter-radiotracer translation offer effective strategies to reduce radiation dose and mitigate tracer availability constraints. Recent self-supervised learning (SSL) foundation models (e.g., DINOv3)...

Pulmonary fluid changes often necessitate treatment replanning; however, associated mass variations compromise deformable dose accumulation (DDA) and complicate its evaluation. Accurate estimation of cumulative dose and its assoc...