% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Ali:851327,
      author       = {Ali, Sharib and Wörz, Stefan and Amunts, Katrin and Eils,
                      Roland and Axer, Markus and Rohr, Karl},
      title        = {{R}igid and non-rigid registration of polarized light
                      imaging data for 3{D} reconstruction of the temporal lobe of
                      the human brain at micrometer resolution},
      journal      = {NeuroImage},
      volume       = {181},
      issn         = {1053-8119},
      address      = {Orlando, Fla.},
      publisher    = {Academic Press},
      reportid     = {FZJ-2018-05013},
      pages        = {235-251},
      year         = {2018},
      abstract     = {To understand the spatial organization as well as long- and
                      short-range connections of the human brain at microscopic
                      resolution, 3D reconstruction of histological sections is
                      important. We approach this challenge by reconstructing
                      series of unstained histological sections of multi-scale
                      (1:3 μm and 64 μm) and multi-modal 3D polarized light
                      imaging (3D-PLI) data. Since spatial coherence is lost
                      during the sectioning procedure, image registration is the
                      major step in 3D reconstruction. We propose a non-rigid
                      registration method which comprises of a novel multi-modal
                      similarity metric and an improved regularization scheme to
                      cope with deformations inevitably introduced during the
                      sectioning procedure, as well as a rigid registration
                      approach using a robust similarity metric for improved
                      initial alignment. We also introduce a multi-scale
                      feature-based localization and registration approach for
                      mapping of 1:3 μm sections to 64 μm sections and a
                      scale-adaptive method that can handle challenging sections
                      with large semi-global deformations due to tissue splits. We
                      have applied our registration method to 126 consecutive
                      sections of the temporal lobe of the human brain with 64 μm
                      and 1:3 μm resolution. Each step of the registration method
                      was quantitatively evaluated using 10 different sections and
                      manually determined ground truth, and a quantitative
                      comparison with previous methods was performed. Visual
                      assessment of the reconstructed volumes and comparison with
                      reference volumes confirmed the high quality of the
                      registration result.},
      cin          = {INM-1 / JARA-HPC},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-1-20090406 / $I:(DE-82)080012_20140620$},
      pnm          = {571 - Connectivity and Activity (POF3-571) / HBP SGA2 -
                      Human Brain Project Specific Grant Agreement 2 (785907) /
                      SMHB - Supercomputing and Modelling for the Human Brain
                      (HGF-SMHB-2013-2017) / 3D Reconstruction of Nerve Fibers in
                      the Human, the Monkey and the Rodent Brain
                      $(jinm11_20171101)$},
      pid          = {G:(DE-HGF)POF3-571 / G:(EU-Grant)785907 /
                      G:(DE-Juel1)HGF-SMHB-2013-2017 /
                      $G:(DE-Juel1)jinm11_20171101$},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:30018015},
      UT           = {WOS:000445165600021},
      doi          = {10.1016/j.neuroimage.2018.06.084},
      url          = {https://juser.fz-juelich.de/record/851327},
}