• DocumentCode
    3069652
  • Title

    Automated detection of white matter abnormality and its application to Alzheimer´s disease

  • Author

    Zhao, Xiaojie ; Wu, Xianjun ; Yao, Li

  • Author_Institution
    Coll. of Inf. Sci. & Technol., Beijing Normal Univ., Beijing, China
  • fYear
    2012
  • fDate
    1-4 July 2012
  • Firstpage
    178
  • Lastpage
    181
  • Abstract
    Diffusion tensor imaging (DTI) technique, which can be used to research the white matter of human brain noninvasively, provides more valuable information in the study of white matter abnormality, especially using fractional anisotropy (FA) images calculated from DTI data. Although there are many different DTI data analysis software, most of them are inconvenient to use and qualitative via visual inspection. To provide assistance to physicians in improving the facilitation and sensitivity of the white matter abnormality analysis, we developed an automated FA analysis method of an individual in comparison with a group of normal controls, which was based on the principle of voxel based analysis (VBA), and contained preprocessing, database, and statistical analysis procedures. Only using FA and Bo images, the final results about the white matter structure difference would be displayed automatically and interactively. Some data generated during the processing were stored to corresponding path and could be checked when necessary. We applied this methods to Alzheimer´s disease (AD). The final result supplied the brain regions where FA values of AD were reduced. DTI data from fifteen AD and sixteen elderly healthy subjects was used to analyse and the brain regions which affected by AD were consonant in the main with the previous study, such as corpus callosum, cingulate regions, and so on. This method could be valuable tool to help physicians in making their clinical decisions.
  • Keywords
    biodiffusion; biomedical MRI; brain; data analysis; diseases; medical image processing; statistical analysis; Alzheimers disease; cingulate regions; corpus callosum; data analysis software; diffusion tensor imaging; fractional anisotropy images; human brain; statistical analysis; visual inspection; voxel based analysis; white matter abnormality automated detection; white matter structure; Alzheimer´s disease; diffusion tensor imaging; fractional anisotropy; voxel based analysis; white matter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Complex Medical Engineering (CME), 2012 ICME International Conference on
  • Conference_Location
    Kobe
  • Print_ISBN
    978-1-4673-1617-0
  • Type

    conf

  • DOI
    10.1109/ICCME.2012.6275656
  • Filename
    6275656