AAPM | COMP Joint Meeting · Vancouver · July 19-22
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To test whether commonly used pixel-wise CT reconstruction metrics reflect preservation of clinically relevant anatomy for radiotherapy imaging, and to develop an anatomy-centered, task-based evaluation and enhancement approach f...
Deep learning–based glioma segmentation models are commonly developed under the assumption that the standard glioma MRI protocol—T1-weighted, contrast-enhanced T1 (T1ce), T2-weighted, and FLAIR—is available; however, this assumpt...
To evaluate whether a Large Language Model (LLM)–driven autonomous planning system can self-learn planning strategies from human planner logs and apply this knowledge to generate clinically compatible radiotherapy plans without m...
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