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1 Journal of Applied Computer Science

1 2005

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A Novel Statistical Approach for Segmentation of Single-Channel Brain MRI Using an Improved EM algorithm

Yang Y., Zheng Ch., Lin P.

Journal of Applied Computer Science

2005

Vol. 13, nr 1

113-125

This paper presents a novel statistical method for segmentation of single-channel brain magnetic resonance (MR) image data. The method based on an improved expectation maximization (EM) algorithm proposed in this paper involves three steps. Firstly, after pre-processing the image with the curvature anisotropic diffusion filter, the background (BG) and brain masks of the image are obtained by applying a combination approach of thresholding with morphology. Secondly, the connected threshold region growing technique is employed to get the preliminary results of white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) on a brain MRI. Finally, the previous results are served as the priori knowledge for the improved EM algorithm to segment the brain MRI. The performance of the proposed method is compared with that of the popular used fuzzy-C means (FCM) segmentation. Experimental results show our approach is effective, robust and significantly faster than the conventional EM based method.