Context‐informed personalized segmentation from radiology reports: A fully automated framework for long‐term liver tumor follow‐up

Abstract

Personalized segmentation has been shown to improve performance over generalized models in follow‐up imaging; however, its robustness across large temporal gaps remains unclear. We propose a fully automated, context‐informed personalization framework that integrates radiology report‐derived clinical context with imaging features to improve longitudinal liver tumor segmentation.