Geometric, dosimetric and psychometric evaluation of three commercial AI software solutions for OAR auto-segmentation in head and neck radiotherapy.

ABSTRACT: Contouring organs-at-risk (OARs) is a critical yet time-consuming step in head and neck (HaN) radiotherapy planning. Auto-segmentation methods have been widely studied, and commercial solutions are increasingly entering clinical use. However, their adoption warrants a comprehensive, multi-perspective evaluation. The purpose of this study is to compare three commercial artificial intelligence (AI) software solutions (Limbus, MIM and MVision) for HaN OAR auto-segmentation on a cohort of 10 computed tomography images with reference contours obtained from the public HaN-Seg dataset, from both observational (descriptive and empirical) and analytical (geometric, dosimetric and psychometric) perspectives. The observational evaluation included vendor questionnaires on technical specifications and

SUBMITTER: Podobnik G 

PROVIDER: S-EPMC12480989 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature