Accurate volume measurement for liver surgery in vivo evaluation with a pig model

Abstract The preoperative measurement of liver volume is a predictive parameter for fewer postoperative complications, especially in living donor liver transplantation. Modern surgery-planning systems estimate these volumes from segmented image data. Most algorithms used for that purpose were evaluated only in the 1970s. This work is a structured analysis of different volume measurement algorithms and their evaluation with an in vivo pig model. We show that the current approaches are not appropriate for accurate volume estimation based on CT images. Therefore, we present a new algorithm that minimizes the measuring error and seems to be robust against inter- and intra-observer variabilities.