Semi-automatic segmentation for prostate interventions

Abstract

In this paper we report and characterize a semi-automatic prostate segmentation method for prostate brachytherapy. Based on anatomical evidence and requirements of the treatment procedure, a warped and tapered ellipsoid was found suitable as the a priori 3D shape of the prostate. By transforming the acquired endorectal transverse images of the prostate into ellipses, the shape fitting problem was cast into a convex problem which can be solved efficiently. The average whole gland error between volumes created from manual and semi-automatic contours from 21 patients was 6.63±0.9%. For use in brachytherapy treatment planning, the resulting contours were modified, if deemed necessary, by radiation oncologists prior to treatment. The average whole gland volume error between the volumes computed from semi-automatic contours and those computed from modified contours, from 40 patients, was 5.82±4.15%. The amount of bias in the physicians’ delineations when given an initial semi-automatic contour was measured by comparing the volume error between 10 prostate volumes computed from manual contours with those of modified contours. This error was found to be 7.25±0.39% for the whole gland. Automatic contouring reduced subjectivity, as evidenced by a decrease in segmentation inter- and intra-observer variability from 4.65% and 5.95% for manual segmentation to 3.04% and 3.48% for semi-automatic segmentation, respectively. We characterized the performance of the method relative to the reference obtained from manual segmentation by using a novel approach that divides the prostate region into nine sectors. We analyzed each sector independently as the requirements for segmentation accuracy depend on which region of the prostate is considered. The measured segmentation time is 14±1 seconds with an additional 32±14 seconds for initialization. By assuming 1–3 minutes for modification of the contours, if necessary, a total segmentation time of less than 4 minutes is required, with no additional time required prior to treatment planning. This compares favorably to the 5–15 minute manual segmentation time required for experienced individuals. The method is currently used at the British Columbia Cancer Agency (BCCA) Vancouver Cancer Centre as part of the standard treatment routine in low dose rate prostate brachytherapy and is found to be a fast, consistent and accurate tool for the delineation of the prostate gland in ultrasound images.

Three-Dimensional Nonrigid MR-TRUS Registration Using Dual Optimization

“…The mean computation time was calculated by running the program for 10 patients. 2) Manual Initialization: We initialized the registration to generate a rigid transform as an initial approximate alignment using six manually placed approximately corresponding landmarks: leftmost, rightmost, topmost, bottommost points on the largest view of the axial slices [35]; the urethra at the entrance into the prostate; and the end point of the peripheral zone at the apex on the 3-D TRUS and MR images. These approximately selected landmarks, such as on the prostate boundary and bladder, are geometric features that can be identified on both modalities.…”

Assistive system based on nerve detection and needle navigation in ultrasound images for regional anesthesia

“…To deal with this problem, many of the methods proposed in the literature have used semi-automatic segmentation (Rabben et al, 2000;Mahdavi et al, 2011;Duarte et al, 2013;Ni et al, 2015), in which a human localizes a suitable region, and then segmentation algorithms delineate the selected region. This study was designed to automatically detect ROIs and delineate their boundaries.…”

Interactive prostate shape reconstruction from 3D TRUS images

“…There have been several published methods on automated or semi-automated reconstruction of 3D prostate shapes [20, 21, 22, 23]. These methods typically create contours by using automated image processing and/or active contours – physically based curve models to create a contour that is of a specified level of smoothness.…”