Diffusion simulation-based fiber tracking using time-of-arrival maps: a comparison with standard methods

  • Sarah C. Mang
  • Dmitriy Logashenko
  • Daniel Gembris
  • Gabriel Wittum
  • Wolfgang Grodd
  • Uwe Klose
Research Article



We propose a new tracking method based on time-of-arrival (TOA) maps derived from simulated diffusion processes.

Materials and methods

The proposed diffusion simulation-based tracking consists of three steps that are successively evaluated on small overlapping sub-regions in a diffusion tensor field. First, the diffusion process is simulated for several time steps. Second, a TOA map is created to store simulation results for the individual time steps that are required for the tract reconstruction. Third, the fiber pathway is reconstructed on the TOA map and concatenated between neighboring sub-regions. This new approach is compared with probabilistic and streamline tracking. All methods are applied to synthetic phantom data for an easier evaluation of their fiber reconstruction quality.


The comparison of the tracking results did show severe problems for the streamline approach in the reconstruction of crossing fibers, for example. The probabilistic method was able to resolve the crossing, but could not handle strong curvature. The new diffusion simulation-based tracking could reconstruct all problematic fiber constellations.


The proposed diffusion simulation-based tracking method used the whole tensor information of a neighborhood of voxels and is, therefore, able to handle problematic tracking situations better than established methods.


Fiber tracking DSBT DTI 


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Copyright information

© ESMRMB 2010

Authors and Affiliations

  • Sarah C. Mang
    • 1
    • 2
    • 3
  • Dmitriy Logashenko
    • 4
  • Daniel Gembris
    • 2
    • 5
  • Gabriel Wittum
    • 6
  • Wolfgang Grodd
    • 1
  • Uwe Klose
    • 1
  1. 1.Section Experimental MR, Department of NeuroradiologyUniversity HospitalTuebingenGermany
  2. 2.Institute for Computational MedicineUniversity MannheimMannheimGermany
  3. 3.E071-SIDT, German Cancer Research CenterHeidelbergGermany
  4. 4.Steinbeis-Forschungszentrum 936Oelbronn-DuerrnGermany
  5. 5.Bruker Biospin MRI GmbHEttlingenGermany
  6. 6.Goethe Center for Scientific Computing (G-CSC), Simulation and ModellingGoethe UniversityFrankfurtGermany

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