DocumentCode
2519473
Title
Segmentation of Brain MR Images Based on T-Mixture Model
Author
Zhao, Haifeng ; Xu, Xingming ; Chen, Sibao ; Luo, Bin
Author_Institution
Key Lab. of Intell. Comput. & Signal Process., Anhui Univ., Hefei, China
fYear
2009
fDate
11-13 June 2009
Firstpage
1
Lastpage
4
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. 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 of brain MR Images based on t-mixture model is outlined follows. The parameters of t-mixture model for the image are firstly estimated. Then the posterior probabilities of the pixels of the image are computed. At last, the image is segmented according to the Bayes decision rule for minimum error. Experimental results show that t-mixture model fits for medical image segmentation.
Keywords
Bayes methods; biomedical MRI; brain; image segmentation; medical image processing; Bayes decision rule; brain MR images; computer-aided diagnosis; magnetic resonance imaging; medical image segmentation; posterior probability; radiological evaluation; t-mixture model; white matter segmentation; Anatomical structure; Biomedical imaging; Brain modeling; Educational technology; Hidden Markov models; Image segmentation; Magnetic resonance imaging; Mathematical model; Medical diagnostic imaging; Surgery;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-2901-1
Electronic_ISBN
978-1-4244-2902-8
Type
conf
DOI
10.1109/ICBBE.2009.5163370
Filename
5163370
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