title: Quantitative analysis in clinical applications of brain MRI using independent component analysis coupled with support vector machine.
abstract: OBJECTIVE
  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.
  
  
  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.
  
  
  CONCLUSIONS
  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.affiliation: Department of Radiology, Taichung Veterans General Hospital, Taichung, Taiwan.
authors.forename: Jyh-Wen
authors.initials: JW
authors.lastname: Chai
authors.forename: Clayton
authors.initials: C
authors.lastname: Chi-Chang Chen
authors.forename: Chih-Ming
authors.initials: CM
authors.lastname: Chiang
authors.forename: Yung-Jen
authors.initials: YJ
authors.lastname: Ho
authors.forename: Hsian-Min
authors.initials: HM
authors.lastname: Chen
authors.forename: Yen-Chieh
authors.initials: YC
authors.lastname: Ouyang
authors.forename: Ching-Wen
authors.initials: CW
authors.lastname: Yang
authors.forename: San-Kan
authors.initials: SK
authors.lastname: Lee
authors.forename: Chein-I
authors.initials: CI
authors.lastname: Chang
mesh_terms: D000328:Adult; D001921:Brain / Q000033:anatomy & histology* / Q000473:pathology*; D001931:Brain Mapping / Q000379:methods* / Q000706:statistics & numerical data; D016002:Discriminant Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000706:statistics & numerical data; D008875:Middle Aged; D015588:Observer Variation; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D055815:Young Adult