Slice-based prostate segmentation in 3D US images based on continuity constraint

Abstract

Slice-based 3D segmentation is a semi-automatic segmentation approach that is used to segment the prostate from 3D ultrasound (US) images. First, the prostate is re-sliced rotationally around a pre-selected rotational axis passing through the approximate center of the prostate. Using a deformable model, an intial guess is used to refine the prostate boundary to better fit the outline of the prostate in an initial 2D slice. Then, the refined contour is propagated to its adjacent slices and deformed. This proceudre is repeated until all slices are segmented. Unfortunately, in this segmentation approach, the segmented contour may not fit the actual prostate boundary properly, propagating the segmentation error and making it larger. In this paper, we add a continuity constraint in the slice-based 3D segmentation approach by using an autoregressive (AR) model to correct the endpoint propagation in a cross-sectional plane perpendicular to the rotational axis. Experiments with 6 patient prostate 3D US images demonstrated that our method can obtain a smooth segmented prostate and the average distance between our algorithmic and the manually segmented 2D prostates on the cross-sectional plane was about 0.8mm less than the distance between the algorithmic segmentation without using the continuity constraint and the manually segmented 2D prostates on the cross-sectional plane.