Document Detail


Quantitative analysis in clinical applications of brain MRI using independent component analysis coupled with support vector machine.
MedLine Citation:
PMID:  20578007     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
PURPOSE: To effectively perform quantification of brain normal tissues and pathologies simultaneously, independent component analysis (ICA) coupled with support vector machine (SVM) is investigated and evaluated for effective volumetric measurements of normal and lesion tissues using multispectral MR images. MATERIALS AND METHODS: Synthetic and real MR data of normal brain and white matter lesion (WML) data were used to evaluate the accuracy and reproducibility of gray matter (GM), white matter (WM), and WML volume measurements by using the proposed ICA+SVM method to analyze three sets of MR images, T1-weighted, T2-weighted, and proton density/fluid-attenuated inversion recovery images. RESULTS: The Tanimoto indexes of GM/WM classification in the normal synthetic data calculated by the ICA+SVM method were 0.82/0.89 for data with 0% noise level. As for clinical MR data experiments, the ICA+SVM method clearly extracted the normal tissues and white matter hyperintensity lesions from the MR images, with low intra- and inter-operator coefficient of variations. CONCLUSION: The experiments conducted provide evidence that the ICA+SVM method has shown promise and potential in applications to classification of normal and pathological tissues in brain MRI.
Authors:
Jyh-Wen Chai; Clayton Chi-Chang Chen; Chih-Ming Chiang; Yung-Jen Ho; Hsian-Min Chen; Yen-Chieh Ouyang; Ching-Wen Yang; San-Kan Lee; Chein-I Chang
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Journal of magnetic resonance imaging : JMRI     Volume:  32     ISSN:  1522-2586     ISO Abbreviation:  J Magn Reson Imaging     Publication Date:  2010 Jul 
Date Detail:
Created Date:  2010-06-29     Completed Date:  2010-10-18     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9105850     Medline TA:  J Magn Reson Imaging     Country:  United States    
Other Details:
Languages:  eng     Pagination:  24-34     Citation Subset:  IM    
Copyright Information:
(c) 2010 Wiley-Liss, Inc.
Affiliation:
Department of Radiology, Taichung Veterans General Hospital, Taichung, Taiwan.
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MeSH Terms
Descriptor/Qualifier:
Adult
Brain / anatomy & histology*,  pathology*
Brain Mapping / methods*,  statistics & numerical data
Discriminant Analysis
Humans
Image Processing, Computer-Assisted / methods
Magnetic Resonance Imaging / methods*,  statistics & numerical data
Middle Aged
Observer Variation
Reproducibility of Results
Sensitivity and Specificity
Young Adult

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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