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@MISC{Schiffer:903075,
      author       = {Schiffer, C. and Brandstetter, A. and Bolakhrif, N. and
                      Mohlberg, H. and Amunts, K. and Dickscheid, T.},
      title        = {{U}ltrahigh resolution 3{D} cytoarchitectonic map of the
                      {LGB} (lam 1-6, {CGL}, {M}etathalamus) created by a
                      {D}eep-{L}earning assisted workflow},
      reportid     = {FZJ-2021-04804},
      year         = {2021},
      abstract     = {This dataset contains automatically created
                      cytoarchitectonic maps of the six distinct layers
                      (LGB-lam1-6) of the lateral geniculate body – LGB (CGL,
                      Metathalamus) in the BigBrain (LGB is equivalent to CGL and
                      can be used as synonyms). Mappings were created using Deep
                      Convolutional Neural networks trained on delineations on
                      every 30th section manually delineated on coronal
                      histological sections of 1 micron resolution. Resulting
                      mappings are available on every section. Maps were
                      transformed to the 3D reconstructed BigBrain space.
                      Individual sections were used to assemble a 3D volume of the
                      area, low quality results were replaced by interpolations
                      between nearest neighboring sections. The volume was then
                      smoothed using an 5³ median filter and largest connected
                      components were identified to remove false positive results.
                      The dataset consists of a HDF5 file containing the volume in
                      RAS dimension ordering (20 micron isotropic resolution,
                      dataset “volume”) and an affine transformation matrix
                      (dataset “affine”). An additional dataset
                      $“interpolation_info”$ contains an integer vector for
                      each section which indicates if a section was interpolated
                      due to low quality results (value 2) or not (value 1).},
      keywords     = {Neuroscience (Other)},
      cin          = {INM-1},
      cid          = {I:(DE-Juel1)INM-1-20090406},
      pnm          = {5254 - Neuroscientific Data Analytics and AI (POF4-525) /
                      HBP SGA3 - Human Brain Project Specific Grant Agreement 3
                      (945539)},
      pid          = {G:(DE-HGF)POF4-5254 / G:(EU-Grant)945539},
      typ          = {PUB:(DE-HGF)32},
      doi          = {10.25493/33Z0-BX},
      url          = {https://juser.fz-juelich.de/record/903075},
}