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 manipulations as well as contour shape modifications. We illustrate the feasibility of our system by providing examples of its application to the extraction of bones, muscles, kidneys with blood vessels, and bowels.
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design