3D prostate surface detection from ultrasound images based on level set method

Abstract

Accurate detection of prostate boundaries is required in many diagnostic and treatment procedures for prostate diseases. In this paper, a new approach based on level set method to perform 3D prostate surface detection from transrectal ultrasound (TRUS) images is presented. Contrary to many other deformable models, level set method offers several advantages such as minimal need for user input, flexible topology, and straightforward extension to 3D. However, it is subject to “boundary leaking” problem for ultrasound image segmentation due to the poor image quality. In this work, we first develop a fast discrimination method to extract the prostate region, then this region information, instead of the spatial image gradient, is incorporated into the level set method to remedy the “boundary leaking” problem. Various experimental results show the effectiveness of the proposed method.