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A digital-twin framework for forecasting treatment-day imaging with contour uncertainty in adaptive proton radiotherapy
Head-and-neck anatomy changes over a six-to-seven-week proton course, and the anatomy of a later week cannot be imaged when the plan is made. We present a digital-twin framework that forecasts a patient's treatment-day anatomy as an ensemble of predicted CTs with propagated contours and quantifies the uncertainty of the forecast contours. The twin is a library of previously treated patients with planning and weekly quality-assurance CTs (QACTs), made patient-specific by a two-step foundation-model deformable registration: a cross-patient field carries each library patient onto the current pati
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- arXiv · AI, language, vision and robotics · 2026-09-21T15:01:12.000Z
First collected: 2026-09-23T06:11:12.848Z. This is not the publication date.