• DocumentCode
    478285
  • Title

    White Matter Fiber Tracts Based On Diffusion Tensor Imaging

  • Author

    Di, Qian ; Wang, Tingting ; Yao, Li ; Zhao, Xiaojie

  • Author_Institution
    Coll. of Inf. Sci. & Technol., Beijing Normal Univ., Beijing
  • Volume
    4
  • fYear
    2008
  • fDate
    18-20 Oct. 2008
  • Firstpage
    306
  • Lastpage
    310
  • Abstract
    The recently developed magnetic resonance imaging technique of diffusion tensor imaging (DTI) has a widespread application on investigating the cerebral white matter architecture. When referred to fiber tracking, as the typical application of DTI, one of the most intuitive ways to reconstruct fiber trajectory is streamline tracking, (STT). Regarding the problems from noise and discrete tensor field in traditional STT algorithm, we introduce the concept of adjacent and previous voxels as well as the break point during fiber tracking. To evaluate the validity of our improved algorithm, we firstly applied it on the simulated data and meanwhile obtained some available values in our approach. Then the traditional STT and improved algorithm were both applied to DTI data to reconstruct the fiber trajectory. The results showed our improved method did follow the actual fiber more precisely. Future improvements were also discussed in the end of the paper.
  • Keywords
    biomedical MRI; brain; image reconstruction; medical image processing; diffusion tensor imaging; image reconstruction; magnetic resonance imaging; streamline tracking; white matter fiber tracts; Data acquisition; Diffusion tensor imaging; Educational institutions; Humans; Image reconstruction; Information science; Laboratories; Magnetic resonance imaging; Neuroscience; Tensile stress; Diffusion Tensor Imaging; Fiber Tracts; White Matter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2008. ICNC '08. Fourth International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-0-7695-3304-9
  • Type

    conf

  • DOI
    10.1109/ICNC.2008.819
  • Filename
    4667295