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@ARTICLE{Oberstrass:1023722,
      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        = {{A}nalyzing {R}egional {O}rganization of the {H}uman
                      {H}ippocampus in 3{D}-{PLI} {U}sing {C}ontrastive {L}earning
                      and {G}eometric {U}nfolding},
      publisher    = {arXiv},
      reportid     = {FZJ-2024-01777},
      year         = {2024},
      abstract     = {Understanding the cortical organization of the human brain
                      requires interpretable descriptors for distinct structural
                      and functional imaging data. 3D polarized light imaging
                      (3D-PLI) is an imaging modality for visualizing fiber
                      architecture in postmortem brains with high resolution that
                      also captures the presence of cell bodies, for example, to
                      identify hippocampal subfields. The rich texture in 3D-PLI
                      images, however, makes this modality particularly difficult
                      to analyze and best practices for characterizing
                      architectonic patterns still need to be established. In this
                      work, we demonstrate a novel method to analyze the regional
                      organization of the human hippocampus in 3D-PLI by combining
                      recent advances in unfolding methods with deep texture
                      features obtained using a self-supervised contrastive
                      learning approach. We identify clusters in the
                      representations that correspond well with classical
                      descriptions of hippocampal subfields, lending validity to
                      the developed methodology.},
      keywords     = {Computer Vision and Pattern Recognition (cs.CV) (Other) /
                      FOS: Computer and information sciences (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) / HIBALL - Helmholtz International BigBrain
                      Analytics and Learning Laboratory (HIBALL) (InterLabs-0015)
                      / EBRAINS 2.0 - EBRAINS 2.0: A Research Infrastructure to
                      Advance Neuroscience and Brain Health (101147319)},
      pid          = {G:(DE-HGF)POF4-5254 / G:(EU-Grant)945539 /
                      G:(DE-HGF)InterLabs-0015 / G:(EU-Grant)101147319},
      typ          = {PUB:(DE-HGF)25},
      doi          = {10.48550/ARXIV.2402.17744},
      url          = {https://juser.fz-juelich.de/record/1023722},
}