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@INPROCEEDINGS{Baker:1032004,
      author       = {Baker, Dirk Norbert and Selzner, Tobias and Göbbert, Jens
                      Henrik and Scharr, Hanno and Riedel, Morris and Hvannberg,
                      Ebba Þóra and Schnepf, Andrea and Zielasko, Daniel},
      title        = {{H}ands-{O}n {P}lant {R}oot {S}ystem {R}econstruction in
                      {V}irtual {R}eality},
      publisher    = {ACM New York, NY, USA},
      reportid     = {FZJ-2024-05920},
      pages        = {1-2},
      year         = {2024},
      comment      = {30th ACM Symposium on Virtual Reality Software and
                      Technology : [Proceedings] - ACM New York, NY, USA, 2024. -
                      ISBN 9798400705359 - doi:10.1145/3641825.3689494},
      booktitle     = {30th ACM Symposium on Virtual Reality
                       Software and Technology : [Proceedings]
                       - ACM New York, NY, USA, 2024. - ISBN
                       9798400705359 -
                       doi:10.1145/3641825.3689494},
      abstract     = {VRoot is an immersive extended reality reconstruction tool
                      for root system architectures from 3D volumetric scans of
                      soil columns. We have conducted a laboratory user study to
                      assess the performance of new users with our software in
                      comparison to established software. We utilize a plant model
                      to derive a synthetic root architecture, providing a
                      baseline for reconstruction. This demo showcases the
                      processes and techniques contributing to exact and efficient
                      manual root architecture reconstruction in Virtual Reality.
                      The extraction task typically is the sparse graph-structure
                      extraction from a 3D magnetic-resonance imaging (MRI) data
                      set. We visualize the RSA directly within the MRI and offer
                      selection-set-based methods of adapting and augmenting the
                      root architecture. This application is in productive use at
                      our partner institute, where it is used to analyze complex
                      root images.},
      month         = {Oct},
      date          = {2024-10-09},
      organization  = {VRST '24: 30th ACM Symposium on
                       Virtual Reality Software and
                       Technology, Trier Germany (Germany), 9
                       Oct 2024 - 11 Oct 2024},
      cin          = {JSC / IBG-3 / IAS-8},
      cid          = {I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)IBG-3-20101118 /
                      I:(DE-Juel1)IAS-8-20210421},
      pnm          = {2A3 - Remote Sensing (CARF - CCA) (POF4-2A3) / 5112 -
                      Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and
                      Research Groups (POF4-511) / 5121 - Supercomputing $\&$ Big
                      Data Facilities (POF4-512) / 2173 - Agro-biogeosystems:
                      controls, feedbacks and impact (POF4-217) / EUROCC-2
                      (DEA02266) / DFG project G:(GEPRIS)390732324 - EXC 2070:
                      PhenoRob - Robotik und Phänotypisierung für Nachhaltige
                      Nutzpflanzenproduktion (390732324)},
      pid          = {G:(DE-HGF)POF4-2A3 / G:(DE-HGF)POF4-5112 /
                      G:(DE-HGF)POF4-5121 / G:(DE-HGF)POF4-2173 /
                      G:(DE-Juel-1)DEA02266 / G:(GEPRIS)390732324},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
      UT           = {WOS:001336540500090},
      doi          = {10.1145/3641825.3689494},
      url          = {https://juser.fz-juelich.de/record/1032004},
}