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@ARTICLE{Dohmen:188078,
      author       = {Dohmen, Melanie and Menzel, Miriam and Wiese, Hendrik and
                      Reckfort, Julia and Hanke, Frederike and Pietrzyk, Uwe and
                      Zilles, Karl and Amunts, Katrin and Axer, Markus},
      title        = {{U}nderstanding fiber mixture by simulation in 3{D}
                      {P}olarized {L}ight {I}maging},
      journal      = {NeuroImage},
      volume       = {111},
      issn         = {1053-8119},
      address      = {Orlando, Fla.},
      publisher    = {Academic Press},
      reportid     = {FZJ-2015-01546},
      pages        = {464–475},
      year         = {2015},
      abstract     = {3D Polarized Light Imaging (3D-PLI) is a neuroimaging
                      technique that has opened up new avenues to study the
                      complex architecture of nerve fibers in postmortem brains.
                      The spatial orientations of the fibers are derived from
                      birefringence measurements of unstained histological brain
                      sections that are interpreted by a voxel-based analysis.
                      This, however, implies that a single fiber orientation
                      vector is obtained for each voxel and reflects the net
                      effect of all comprised fibers. The mixture of various fiber
                      orientations within an individual voxel is a priori not
                      accessible by a standard 3D-PLI measurement. In order to
                      better understand the effects of fiber mixture on the
                      measured 3D-PLI signal and to improve the interpretation of
                      real data, we have developed a simulation method referred to
                      as SimPLI. By means of SimPLI, it is possible to reproduce
                      the entire 3D-PLI analysis starting from synthetic fiber
                      models in user-defined arrangements and ending with
                      measurement-like tissue images. For the simulation, each
                      synthetic fiber is considered as an optical retarder, i.e.,
                      multiple fibers within one voxel are described by multiple
                      retarder elements. The investigation of different synthetic
                      crossing fiber arrangements generated with SimPLI
                      demonstrated that the derived fiber orientations are
                      strongly influenced by the relative mixture of crossing
                      fibers. In case of perpendicularly crossing fibers, for
                      example, the derived fiber direction corresponds to the
                      predominant fiber direction. The derived fiber inclination
                      turned out to be not only influenced by myelin density but
                      also systematically overestimated due to signal attenuation.
                      Similar observations were made for synthetic models of optic
                      chiasms of a human and a hooded seal which were opposed to
                      experimental 3D-PLI data sets obtained from the chiasms of
                      both species. Our study showed that SimPLI is a powerful
                      method able to test hypotheses on the underlying fiber
                      structure of brain tissue and, therefore, to improve the
                      reliability of the extraction of nerve fiber orientations
                      with 3D-PLI},
      cin          = {INM-1 / INM-4},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-1-20090406 / I:(DE-Juel1)INM-4-20090406},
      pnm          = {574 - Theory, modelling and simulation (POF3-574) / SMHB -
                      Supercomputing and Modelling for the Human Brain
                      (HGF-SMHB-2013-2017) / HBP - The Human Brain Project
                      (604102)},
      pid          = {G:(DE-HGF)POF3-574 / G:(DE-Juel1)HGF-SMHB-2013-2017 /
                      G:(EU-Grant)604102},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000352224100041},
      doi          = {10.1016/j.neuroimage.2015.02.020},
      url          = {https://juser.fz-juelich.de/record/188078},
}