Efficient Construction of Geometric Nerve Fiber Models for Simulation with 3D-PLI

  • Jan A. ReuterEmail author
  • Felix Matuschke
  • Nicole Schubert
  • Markus Axer
Conference paper
Part of the Informatik aktuell book series (INFORMAT)


Three-dimensional (3D) polarized light imaging (PLI) is an unique technique used to reconstruct nerve fiber orientations of postmortem brains at ultra-high resolution. To continuously improve the current physical model of 3D-PLI, simulations are powerful methods. Since the creation of simulated data can be time consuming, we developed a tool which enables fast and efficient creation of synthetic fiber data using parametric functions and interpolation methods. Performance tests showed that every component of the program scales linearly with the amount of fiber points while the reconstructed fiber cup phantom and optic chiasm-like crossing fiber models reproduce known effects known from 3D-PLI measurements.


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  1. 1.
    Axer M, Amunts K, Grassel D, et al. A novel approach to the human connectome: ultra-high resolution mapping of fiber tracts in the brain. Neuroimage. 2011;54(2):1091-1101.CrossRefGoogle Scholar
  2. 2.
    Dohmen M, Menzel M, et al HW. Understanding fiber mixture by simulation in 3D polarized light imaging. Neuroimage. 2015;111:464-475.CrossRefGoogle Scholar
  3. 3.
    Menzel M, Axer M, De Raedt He. Finite-Difference Time-Domain Simulation for Three-Dimensional Polarized Light Imaging. Cham: Springer International; 2016.Google Scholar
  4. 4.
    Jones RC. A new calculus for the treatment of optical systemsIII. The sohncke theory of optical activity. J Opt Soc Am. 1941 Jul;31(7):500-503.CrossRefGoogle Scholar
  5. 5.
    F NP, B LF, et al SB. Fiberfox: facilitating the creation of realistic white matter software phantoms. Magn Reson Med. 2013;72(5):1460-1470.Google Scholar
  6. 6.
    Fillard P, Descoteaux M, et al AG. Quantitative evaluation of 10 tractography algorithms on a realistic diffusion MR phantom. Neuroimage. 2011;56(1):220-234.CrossRefGoogle Scholar

Copyright information

© Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2019

Authors and Affiliations

  • Jan A. Reuter
    • 1
    Email author
  • Felix Matuschke
    • 1
  • Nicole Schubert
    • 1
  • Markus Axer
    • 1
  1. 1.Institute of Neuroscience and Medicine (INM-1)Forschungszentrum JülichJülichDeutschland

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