Automated grading of venous beading
Computers and Biomedical Research
Operations Useful for Similarity-Invariant Pattern Recognition
Journal of the ACM (JACM)
Segmentation of 3D Brain Structures Using Level Sets and Dense Registration
MMBIA '00 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
Segmentation of CT Brain Images Using K-Means and EM Clustering
CGIV '08 Proceedings of the 2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation
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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.