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@MISC{Oberstra:1034464,
      author       = {Oberstraß, Alexander and DeKraker, Jordan and
                      Palomero-Gallagher, Nicola and Muenzing, Sascha E. A. and
                      Evans, Alan C. and Axer, Markus and Amunts, Katrin and
                      Dickscheid, Timo},
      title        = {{D}eep texture features for surface-based characterization
                      of fiber architecture in the human hippocampus (v1)},
      publisher    = {EBRAINS},
      reportid     = {FZJ-2024-07230},
      year         = {2024},
      abstract     = {This dataset contains deep texture features characterizing
                      architectonic patterns of the pyramidal layer in the
                      hippocampal cornu Ammonis region and the subicular complex,
                      as captured by three-dimensional polarized light imaging
                      (3D-PLI). The 3D-PLI measurements were obtained from 547
                      individual brain sections of the right hippocampus of an
                      87-year-old male. Texture features were extracted from
                      3D-PLI images using a width-reduced ResNet-50 encoder
                      trained on a 3D-Context Contrastive Learning (CL-3D)
                      objective. The features were aggregated along the full depth
                      of the pyramidal layer and transformed into an unfolded
                      coordinate space using HippUnfold. In addition, we provide
                      projections of the feature vectors onto 52 principal
                      components with largest explained variance. These components
                      reflect the general regional organization and reveal an
                      expected functional rostro-caudal heterogeneity of the
                      pyramidal layer. By transferring features to an unfolded
                      coordinate system using HippUnfold, the data are placed in a
                      canonical reference space, enabling comparisons with other
                      unfolded datasets. Moreover, we provide unfolded surfaces
                      for both the MNI ICBM 152 Nonlinear Asymmetric 2009c and the
                      BigBrain histological space, allowing access to the features
                      within these volumetric reference spaces as well.},
      keywords     = {Neuroscience (Other)},
      cin          = {INM-1},
      cid          = {I:(DE-Juel1)INM-1-20090406},
      pnm          = {5251 - Multilevel Brain Organization and Variability
                      (POF4-525) / HIBALL - Helmholtz International BigBrain
                      Analytics and Learning Laboratory (HIBALL) (InterLabs-0015)
                      / HBP SGA3 - Human Brain Project Specific Grant Agreement 3
                      (945539) / EBRAINS 2.0 - EBRAINS 2.0: A Research
                      Infrastructure to Advance Neuroscience and Brain Health
                      (101147319)},
      pid          = {G:(DE-HGF)POF4-5251 / G:(DE-HGF)InterLabs-0015 /
                      G:(EU-Grant)945539 / G:(EU-Grant)101147319},
      typ          = {PUB:(DE-HGF)32},
      doi          = {10.25493/T1N3-KCX},
      url          = {https://juser.fz-juelich.de/record/1034464},
}