Medical volume images contain ambiguous and low-contrast boundaries around which existing fully- or semiautomatic segmentation algorithms often cause errors. In this paper, we propose a novel system for intuitively and efficiently refining medical volume segmentation by modifying multiple curved contours. Starting with segmentation data obtained using any existing algorithm, the user places a three-dimensional curved cross-section and contours of the foreground region by drawing a cut stroke, and then modifies the contours referring to the cross-section. The modified contours are used as constraints for deforming a boundary surface that envelops the foreground region, and the region is updated by that deformed boundary. Our surface deformation algorithm seamlessly integrates detail-preserving and curvature-diffusing methods to keep important detail boundary features intact while obtaining smooth surfaces around unimportant boundary regions. Our system supports topological manipulation...