Reiter, OliverBreeuwer, MarcelGröller, EduardRaidou, Renata GeorgiaJimmy Johansson and Filip Sadlo and Tobias Schreck2018-06-022018-06-022018978-3-03868-060-4https://doi.org/10.2312/eurovisshort.20181075https://diglib.eg.org:443/handle/10.2312/eurovisshort20181075In prostate cancer treatment, automatic segmentations of the pelvic organs are often used as input to radiotherapy planning systems. However, natural anatomical variability of the involved organs is a common reason, for which segmentation algorithms fail, introducing errors in the radiotherapy treatment procedure, as well. Understanding how the shape and size of these organs affect the accuracy of segmentation is of major importance for developers of segmentation algorithms. However, current means of exploration and analysis provide limited insight. In this work, we discuss the design and implementation of a web-based framework, which enables easy exploration and detailed analysis of shape variability, and allows the intended users - i.e., segmentation experts - to generate hypotheses in relation to the performance of the involved algorithms. Our proposed approach was tested with segmentation meshes from a small cohort of 17 patients. Each mesh consists of four pelvic organs and two organ interfaces, which are labeled and have per-triangle correspondences. A usage scenario and an initial informal evaluation with a segmentation expert demonstrate that our framework allows the developers of the algorithms to quickly identify inaccurately segmented organs and to deliberate about the relation of variability to anatomical features and segmentation quality.Humancentered computingVisual analyticsApplied computingLife and medical sciences10.2312/eurovisshort.2018107537-41