Prostate surface segmentation from 3D ultrasound images

Segmenting, or outlining, the prostate boundary is a very important task in diagnosing and treating cancer. In this paper, an algorithm is described for semiautomatic segmentation of the prostate from 3D ultrasound images. The algorithm uses model-based initialization and mesh refinement using an efficient deformable model. Initialization requires the user to select only six points from which the outline of the prostate is estimated using shape information. The estimated outline is then automatically deformed to better fit the prostate boundary. The performance of the algorithm with a single user was compared to manual outlining by the same user. The average distance between semiautomatically and manually outlined boundaries was found to be 1.19 mm, and the average difference in volumes was 7.2%.