Article

SCARF: Auto-Segmentation Clinical Acceptability & Reproducibility Framework for Benchmarking Essential Radiation Therapy Targets in Head and Neck Cancer

2022-01-25

Abstract excerpt

<h4>Background: </h4> and Purpose: Auto-segmentation of organs at risk (OAR) in cancer patients is essential for enhancing radiotherapy planning efficacy and reducing inter-observer variability. Deep learning auto-segmentation models have shown promise, but their lack of transparency and reproducibility hinders their generalizability and clinical acceptability, limiting their use in clinical settings. <h4>Material...

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Literature Corpus work: 92a720a3-2dd1-5096-b148-062986d7b51d
DOI: 10.1101/2022.01.15.22269276

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