Evaluation of algorithms for segmentation of the prostate boundary from 3D ultrasound images

Abstract

We evaluated three algorithms for prostate boundary segmentation from 3D ultrasound images. In the parallel segmentation method, the 3D image was sliced into parallel, contiguous 2D images, whereas in the rotational method, the image was sliced in a rotational manner. Using either method, four points were selected on a central slice and used to initiate a 2D deformable model. The segmented contour was propagated to adjacent slices until the entire prostate was segmented. In the volume-based method, the 3D image was segmented directly without slicing it. Each segmentation algorithm was applied to four 3D images, and the results were compared to manual segmentation. Average volume errors of -8.58%, -1.95% and -5.01% were estimated for the parallel, rotational and volume-based methods, respectively. Approximately 20% of the slices required editing in the parallel method, whereas 13% required editing in the rotational method. Although only one surface segmented using the volume-based method needed editing, manual editing was difficult in 3D. Segmentation times, including editing, ranged from 42 to 82 seconds for the parallel method, from 27 to 52 seconds for the rotational method, and up to 55 seconds for the volume-based method. Based on these results, we recommend the rotational segmentation method.