• DocumentCode
    2582587
  • Title

    Automatic classification of Alzheimer´s patients and age-matched healthy subjects using independent component analysis

  • Author

    Yang, Wenlu ; Li, Xiaojuan ; Huang, Xudong

  • Author_Institution
    Inf. Eng. Coll., Maritime Univ., Shanghai, China
  • Volume
    1
  • fYear
    2011
  • fDate
    15-17 Oct. 2011
  • Firstpage
    151
  • Lastpage
    154
  • Abstract
    In this paper, we proposed an automated novel method combining independent component analysis and voxel of interest for classification of MRI scans of Alzheimer patients and healthy subjects. The method mainly includes five steps: preprocessing of MR images, segmentation of gray matter of the brain, decomposition using independent component analysis, extraction of voxel of interest, and classification by a support vector machine classifier. The automated method of selection of voxel of interest has no disadvantages of manual voxel of interest, such as labor-intensive and time-consuming. The experimental results indicate that the proposed method is able to provide better classification results than that in some previously related works.
  • Keywords
    biomedical MRI; brain; diseases; feature extraction; image classification; image segmentation; independent component analysis; medical image processing; support vector machines; Alzheimer patients; MRI; age-matched healthy subjects; automated novel method; automatic classification; brain; decomposition; gray matter; image classification; image segmentation; independent component analysis; support vector machine classifier; Accuracy; Alzheimer´s disease; Feature extraction; Independent component analysis; Magnetic resonance imaging; Sensitivity; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Informatics (BMEI), 2011 4th International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-9351-7
  • Type

    conf

  • DOI
    10.1109/BMEI.2011.6098235
  • Filename
    6098235