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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. The paper concerns medical image segmentation based on t-mixture model because of merits of the model. By analyzing the features of MR images, the main procedure of white matter segmentation...
This paper presents a fully-automatic and robust MRI segmentation method for brain tissues. The proposed method classifies the brain MRI volume to 4 classes: white matter tissue (WM), gray matter tissue (GM), cerebrospinal fluid (CSF), and the remaining tissues as non-brain tissues (NBT). We utilize the pre-segmented volumes to determine statistically the prior probability for each class, prior information...
Segmentation of MRI brain images plays a critical role in medical image processing and analysis. In this paper, a new method based on Markov Random Field (MRF) is proposed for segmentation of MR brain images. We consider the low-level MRF as a linear combination of Gaussians (LCG) with positive and negative component, and we use the modified Expectation-maximization (MEM) algorithm to estimate the...
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