Validation of Liver Tumor Segmentation in CT Scans by Relating Manual and Algorithmic Performance - A Preliminary Study

The development of segmentation algorithms for liver tumors in CT scans has found growing attention in recent years. The validation of these methods, however, is often treated as a subordinate task. In this article, we review existing approaches and present rst steps towards a new methodology that evaluates the quality of an algorithm in rela- tion to the variability of manual delineations. We obtained three manual segmentations for 50 liver lesions and computed the results of a segmen- tation algorithm. We compared all four masks with each other and with di erent ground truth estimates and calculated scores according to the validation framework from the MICCAI challenge 2008. Our results show some cases where this more elaborate evaluation re ects the segmenta- tion quality in a more adequate way than traditional approaches. The concepts can also be extended to other similar segmentation problems.