In search of truth: Evaluating concordance of AI-based anatomy segmentation models
This paper introduces a practical framework for evaluating concordance among AI-based anatomy segmentation models on datasets lacking ground truth by harmonizing outputs into a standard representation and providing interactive visualization tools, demonstrating its utility in comparing six open-source models on NLST CT scans to flag discrepancies and prioritize cases of inter-model disagreement for expert review.
Lena Giebeler, Deepa Krishnaswamy, David Clunie, Jakob Wasserthal, Lalith Kumar Shiyam Sundar, Andres Diaz-Pinto, Klaus H. Maier-Hein, Murong Xu, Bjoern Menze, Steve Pieper, Ron Kikinis, Andrey Fedoro (…)2026-04-08✓ Author reviewed ⓘ⚡ eess