Abstract: An automated post-processing tool to assess the quality of deep learning-based organ segmentation in medical images is described. According to an example, a method comprises determining, by a system comprising a processor, current values of defined features of respective segmentation masks generated for different anatomical structures included in medical image data via auto-segmentation of the medical image data. The method further comprises determining, by the system, respective measures of correspondence between the current values and corresponding reference values determined for the defined features, determining one or more measures of quality of the auto-segmentation based on the respective measures of correspondence, generating quality assessment report data for the auto-segmentation comprising the one or more measures of quality in standard format that can be displayed by standard clinical software.