Ventricle Boundary in CT: Partial Volume Effect and Local Thresholds

Abstract

We present a mathematical frame to carry out segmentation of cerebrospinal fluid (CSF) of ventricular region in computed tomography (CT) images in the presence of partial volume effect (PVE). First, the image histogram is fitted using the Gaussian mixture model (GMM). Analyzing the GMM, we find global threshold based on parameters of distributions for CSF, and for the combined white and grey matter (WGM). The parameters of distribution of PVE pixels on the boundary of ventricles are estimated by using a convolution operator. These parameters are used to calculate local thresholds for boundary pixels by the analysis of contribution of the neighbor pixels intensities into a PVE pixel. The method works even in the case of an almost unimodal histogram; it can be useful to analyze the parameters of PVE in the ground truth provided by the expert.

Figure 1

CT slice to extract ventricles.

Figure 2

GMM with 3 components for CT slice; HUs from 1 to 75 are given, and the vertical axis is the probability.

Figure 3

Ventricle extraction: (a) original ventricles in CT, (b) the contour of the GT marked, (c) the result of the thresholding, (d) result of smoothing using snake, and (e) the contour (grey line) of ventricle received by algorithm overlapped over the GT (white area).