• DocumentCode
    1814045
  • Title

    Application of Averaged Learning Subspace Method in MRI Classification

  • Author

    Wang, Chuin-Mu ; Chen, Jau-An ; Chu, Jui-Hsing

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Chin-Yi Univ. of Technol., Taichung, Taiwan
  • Volume
    1
  • fYear
    2009
  • fDate
    18-20 Aug. 2009
  • Firstpage
    559
  • Lastpage
    562
  • Abstract
    The objective of this paper is to establish an "averaged learning subspace method" (ALSM) applicable for classification of multi-spectral MR images. By using the ALSM to process the massive amounts of information in multi-spectral MR images, and classification tissues of brain. The classification result of each tissue has shown by binary image, respectively. The classification results would assist doctor to diagnose more efficiently and more accurately and thus to gain more time for necessary action. In order to further evaluate the performance of ALSM, the high order statistics is adopted assessment and compare with perceptron neural network.
  • Keywords
    biological tissues; biomedical MRI; brain; higher order statistics; image classification; learning (artificial intelligence); medical image processing; perceptrons; ALSM; averaged learning subspace method; binary image; brain tissue; high order statistics; medical diagnosis; multispectral MRI image classification; perceptron neural network; Biomedical imaging; Blood; Computed tomography; Covariance matrix; Hospitals; Laser radar; Magnetic resonance imaging; Statistics; Testing; X-rays; ALSM; Classification; MRI;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Assurance and Security, 2009. IAS '09. Fifth International Conference on
  • Conference_Location
    Xian
  • Print_ISBN
    978-0-7695-3744-3
  • Type

    conf

  • DOI
    10.1109/IAS.2009.275
  • Filename
    5283796