• DocumentCode
    2510982
  • Title

    Dyslexia Diagnostics by Centerline-Based Shape Analysis of the Corpus Callosum

  • Author

    Elnakib, Ahmed ; El-Baz, Ayman ; Casanova, Manuel F. ; Switala, A.E.

  • Author_Institution
    Bioeng. Dept., Univ. of Louisville, Louisville, KY, USA
  • fYear
    2010
  • fDate
    23-26 Aug. 2010
  • Firstpage
    261
  • Lastpage
    264
  • Abstract
    Dyslexia severely impairs learning abilities, so that improved diagnostic methods are called for. Neuropathological studies have revealed abnormal anatomy of the Corpus Callosum (CC) in dyslexic brains. We explore a possibility of distinguishing between dyslexic and normal (control) brains by quantitative CC shape analysis in 3D magnetic resonance images (MRI). Our approach consists of the three steps: (i) segmenting the CC from a given 3D MRI using the learned CC shape and visual appearance; (ii) extracting the centerline of the CC; and (iii) classifying the subject as dyslexic or normal based on the estimated length of the CC centerline using a _-nearest neighbor classifier. Experiments revealed significant differences (at the 95% confidence level) between the CC centerlines for 14 normal and 16 dyslexic subjects. Our initial classification suggests the proposed centerline-based shape analysis of the CC is a promising supplement to the current dyslexia diagnostics.
  • Keywords
    biomedical MRI; image classification; image segmentation; medical image processing; patient diagnosis; 3D MRI; 3D magnetic resonance images; CC classification; CC segmentation; CC shape analysis; Neuropathological studies; centerline-based shape analysis; corpus callosum; dyslexia diagnosis; dyslexic brains; k-nearest neighbor classifier; Accuracy; Image segmentation; Magnetic resonance imaging; Shape; Solid modeling; Three dimensional displays; Training; Diagnosis; Dyslexia; and Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2010 20th International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-7542-1
  • Type

    conf

  • DOI
    10.1109/ICPR.2010.73
  • Filename
    5597588