NDLI: Brain MR image segmentation based on Gaussian mixture model with spatial information

Content Provider	IEEE Xplore Digital Library
Author	Feng Zhu Yuqing Song Jianmei Chen
Copyright Year	2010
Description	Author affiliation: Faculty of Science, Jiangsu University, Zhenjiang, P.R. China (Feng Zhu; Yuqing Song; Jianmei Chen)
Abstract	As magnetic resonance imaging (MRI) is an important technology of radiological evaluation and computer-aided diagnosis, the accuracy of the MR image segmentation directly influences the validity of following processing. In general, the Gaussian mixture model (GMM) is highly effective for MR image segmentation. But for the conventional GMM appling in image segmentation, cluster assignment is based solely on the distribution of pixel attributes in the feature space, and the spatial distribution of pixels in an image is not taken into consideration. In this paper, we present a novel GMM scheme by utilizing local contextual information and the high inter-pixel correlation inherent for the segmentation of brain MR image. Firstly, a local spatial function is established, and the class probabilities of very pixels according to bayesian rules are determined adaptively based on local spatial function. Secondly, Expectation Maximization algorithm as an optimization method is used to obtain iterative formula of E-step and M-step for the proposed model Finally, the segmentation experiments by synthetic image and real image demonstrate that the proposed method can get a better classification result.
Starting Page	1346
Ending Page	1350
File Size	353614
Page Count	5
File Format	PDF
ISBN	9781424465132
e-ISBN	9781424465163
DOI	10.1109/CISP.2010.5648022
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Adaptation model Noise image segmentation Brain modeling Classification algorithms spatial information EM algorithm Pixel Gaussian mixture model
Content Type	Text
Resource Type	Article

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