• DocumentCode
    3247630
  • Title

    Oriented tensor reconstruction: tracing neural pathways from diffusion tensor MRI

  • Author

    Zhukov, Leonid ; Barr

  • Author_Institution
    Dept. of Comput. Sci., California Inst. of Technol., Pasadena, CA, USA
  • fYear
    2002
  • fDate
    1-1 Nov. 2002
  • Firstpage
    387
  • Lastpage
    394
  • Abstract
    In this paper we develop a new technique for tracing anatomical fibers from 3D tensor fields. The technique extracts salient tensor features using a local regularization technique that allows the algorithm to cross noisy regions and bridge gaps in the data. We applied the method to human brain DT-MRI data and recovered identifiable anatomical structures that correspond to the white matter brain-fiber pathways. The images in this paper are derived from a dataset having 121×88×60 resolution. We were able to recover fibers with less than the voxel size resolution by applying the regularization technique, i.e., using a priori assumptions about fiber smoothness. The regularization procedure is done through a moving least squares filter directly incorporated in the tracing algorithm.
  • Keywords
    biomedical MRI; data visualisation; eigenvalues and eigenfunctions; interpolation; least squares approximations; 3D tensor fields; a priori assumptions; anatomical fibers tracing; brain-fiber pathways; computer graphics; diffusion tensor MRI; human brain DT-MRI data; identifiable anatomical structures; least squares filter; neural pathways tracing; oriented tensor reconstruction; voxel size resolution; Anatomical structure; Bridges; Data mining; Diffusion tensor imaging; Feature extraction; Humans; Image reconstruction; Magnetic resonance imaging; Neural pathways; Tensile stress;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visualization, 2002. VIS 2002. IEEE
  • Conference_Location
    Boston, MA, USA
  • Print_ISBN
    0-7803-7498-3
  • Type

    conf

  • DOI
    10.1109/VISUAL.2002.1183799
  • Filename
    1183799