Diffusion simulation-based fiber tracking using time-of-arrival maps: a comparison with standard methods |
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Authors: | Sarah C Mang Dmitriy Logashenko Daniel Gembris Gabriel Wittum Wolfgang Grodd Uwe Klose |
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Affiliation: | 1. Section Experimental MR, Department of Neuroradiology, University Hospital, Tuebingen, Germany 2. Institute for Computational Medicine, University Mannheim, Mannheim, Germany 3. E071-SIDT, German Cancer Research Center, Im Neuenheimer Feld 280, 69120, Heidelberg, Germany 4. Steinbeis-Forschungszentrum 936, Oelbronn-Duerrn, Germany 5. Bruker Biospin MRI GmbH, Ettlingen, Germany 6. Goethe Center for Scientific Computing (G-CSC), Simulation and Modelling, Goethe University, Frankfurt, Germany
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Abstract: | Object 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. Results 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. Conclusion 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. |
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