Computerized liver volumetry has been studied, because the current “gold-standard” manual volumetry is subjective and very time-consuming. Liver volumetry is done in either CT or MRI. A number of researchers have developed computerized liver segmentation in CT, but there are fewer studies on ones for MRI. Our purpose in this study was to develop a general framework for liver segmentation in both CT and MRI. Our scheme consisted of 1) an anisotropic diffusion filter to reduce noise while preserving liver structures, 2) a scale-specific gradient magnitude filter to enhance liver boundaries, 3) a fast-marching algorithm to roughly determine liver boundaries, and 4) a geodesic-active-contour model coupled with a level-set algorithm to refine the initial boundaries. Our CT database contained hepatic CT scans of 18 liver donors obtained under a liver transplant protocol. Our MRI database contains 23 patients with 1.5T MRI scanners. To establish “gold-standard” liver volumes, radiologists manually traced the contour of the liver on each CT or MR slice. We compared our computer volumetry with “gold-standard” manual volumetry. Computer volumetry in CT and MRI reached excellent agreement with manual volumetry (intra-class correlation coefficient = 0.94 and 0.98, respectively). Average user time for computer volumetry in CT and MRI was 0.57 ± 0.06 and 1.0 ± 0.13 min. per case, respectively, whereas those for manual volumetry were 39.4 ± 5.5 and 24.0 ± 4.4 min. per case, respectively, with statistically significant difference (p <; .05). Our computerized liver segmentation framework provides an efficient and accurate way of measuring liver volumes in both CT and MRI.