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@MISC{Schiffer:911542,
      author       = {Schiffer, Christian and Bruno, Ariane and Amunts, Katrin
                      and Dickscheid, Timo},
      title        = {{U}ltrahigh-resolution 3{D} cytoarchitectonic map of {A}rea
                      {MFG}1 of the human anterior dorsolateral prefrontal cortex
                      ({DLPFC}) created by a {D}eep-{L}earning assisted workflow
                      (v1)},
      publisher    = {EBRAINS},
      reportid     = {FZJ-2022-04802},
      year         = {2022},
      abstract     = {This dataset contains automatically created detailed map of
                      the area MFG1 of the human anterior dorsolateral prefrontal
                      cortex (DLPFC) in the BigBrain dataset. The mappings were
                      created using Deep Convolutional Neural Networks based on
                      Schiffer et al. 2021, which were trained on delineations on
                      at least every 30th section created based on Bruno et al.
                      2022. Mappings are available on every section. Their quality
                      was observed by a trained neuroscientist to exclude sections
                      with low-quality results from further processing. Automatic
                      mappings were transformed to the 3D reconstructed BigBrain
                      space using transformations used in Amunts et al. 2013,
                      which were provided by Claude Lepage (McGill). Mappings on
                      individual sections were used to assemble 3D volumes of all
                      areas. Low-quality results were replaced by interpolation
                      between nearest neighboring sections. The volumes were then
                      smoothed using a 3D median filter, and the largest connected
                      components were identified to remove false positive results
                      of the classification algorithm. The dataset consists of an
                      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 with an integer value for each section which
                      indicates if a section was replaced by interpolation due to
                      low-quality results (value 2) or not (value 1). Due to the
                      large size of the volume, it is recommended to view the data
                      online using the provided viewer link.},
      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/JN40-NCG},
      url          = {https://juser.fz-juelich.de/record/911542},
}