Fusion of Ultrasound B-Mode and Vibro-Elastography Images for Automatic 3-D Segmentation of the Prostate

Prostate segmentation in B-mode images is a challenging task even when done manually by experts. In this paper, we propose a 3-D automatic prostate segmentation algorithm which makes use of information from both ultrasound B-mode and vibro-elastography data. We exploit the high contrast-to-noise ratio of vibro-elastography images of the prostate, in addition to the commonly used B-mode images, to implement a 2-D active shape model (ASM)-based segmentation algorithm on the mid-gland image. The prostate model is deformed by a combination of two measures: the gray level similarity and the continuity of the prostate edge in both image types. The automatically obtained mid-gland contour is then used to initialize a 3-D segmentation algorithm which models the prostate as a tapered and warped ellipsoid. Vibro-elastography images are used in addition to ultrasound images to improve boundary detection. We report a Dice similarity coefficient of 0.87 $\pm$ 0.07 and 0.87 $\pm$ 0.08 comparing the 2-D automatic contours with manual contours of two observers on 61 images. For 11 cases, a whole gland volume error of 10.2 $\pm$ 2.2% and 13.5 $\pm$ 4.1% and whole gland volume difference of $-7.2\pm 9.1%$ and $-13.3\pm 12.6%$ between 3-D automatic and manual surfaces of two observers is obtained. This is the first validated work showing the fusion of B-mode and vibro-elastography data for automatic 3-D segmentation of the prostate.