  In this paper, a multi-scale framework with local region based active contour
and boundary shape similarity constraint is proposed for the segmentation of
levator hiatus in ultrasound images. In this paper, we proposed a multiscale
active contour framework to segment levator hiatus ultrasound images by
combining the local region information and boundary shape similarity
constraint. In order to get more precisely initializations and reduce the
computational cost, Gaussian pyramid method is used to decompose the image into
coarse-to-fine scales. A localized region active contour model is firstly
performed on the coarsest scale image to get a rough contour of the levator
hiatus, then the segmentation result on the coarse scale is interpolated into
the finer scale image as the initialization. The boundary shape similarity
between different scales is incorporate into the local region based active
contour model so that the result from coarse scale can guide the contour
evolution at finer scale. By incorporating the multi-scale and boundary shape
similarity, the proposed method can precisely locate the levator hiatus
boundaries despite various ultrasound image artifacts. With a data set of 90
levator hiatus ultrasound images, the efficiency and accuracy of the proposed
method are validated by quantitative and qualitative evaluations (TP, FP, Js)
and comparison with other two state-of-art active contour segmentation methods
(C-V model, DRLSE model).
