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This module implements the Finsler tractography method with HARDI data described by J. Melonakos et al. From a set of seeding and target points, the paths are estimated as the shortest path taking into account a local, directional dependent cost.  This module implements the Finsler tractography method with HARDI data described by J. Melonakos et al. From a set of seeding and target points, the paths are estimated as the shortest path taking into account a local, directional dependent cost.  
−  The output provided is the connectivity map from each voxel in the volume to the seeding points, plus a vector volume with the directions tangent to the fiber bundles at each point.  +  The output provided is the connectivity map from each voxel in the volume to the seeding points, plus a vector volume with the directions tangent to the fiber bundles at each point. These directions can be traced back to actually compute the fiber bundles using [[Documentation/{{documentation/version}}/Modules/FinslerBacktracingFinsler Backtracing Module]]. <br> 
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+  The Finsler Tractography Module module uses the fastsweeping algorithm to find the connectivity from a set of seeding points to each voxel in the input DWI volume (or inside the mask, if provided). This connectivity is the minimum cost of arriving at each voxel from the seeds, following the trajectory of the estimated pathways. The cost is computed as the integral along the pathway of a local directional cost computed from the ODF or some other HARDIrelated measurement. A complete description of the algorithm may be found in: J. Melonakos, E. Pichon, S. Angenent, A. Tannenbaum, 'Finsler Active Contours'. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(3):412423. March 2008. A backgroundremoval mask can be used to accelerate computations. Optionally, the algorithm provides at each voxel an estimation of the vector tangent to the optimal pathway at that point (arrival direction). Fastsweeping is full multithreaded, and some other accelerations (checking only those voxels in the causal direction of the solution) have been implemented to obtain a result in a reasonable time. However, an algorithm virtually identical to that in the aforementioned paper may be reproduced fixing the advanced parameters as follows: Cost: (E(q)/Phi(r))^3 Directions: 26 Use threads: deactivate Use accelerated iterations: deactivate (Start accelerated iterations becomes irrelevant). <br>  
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* GJ. Melonakos, E. Pichon, S. Angenent, A. Tannenbaum, 'Finsler Active Contours'. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(3):412423. March 2008  * GJ. Melonakos, E. Pichon, S. Angenent, A. Tannenbaum, 'Finsler Active Contours'. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(3):412423. March 2008  
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Latest revision as of 16:24, 2 May 2014
Home < Documentation < Nightly < Modules < FinslerTractography
For the stable Slicer documentation, visit the 4.10 page. 
Introduction and Acknowledgements
Acknowledgments:
Supported by grant number FMECD2010/71131616E from the Spanish Ministry of Education/Fulbright Committee  

Module Description
This module implements the Finsler tractography method with HARDI data described by J. Melonakos et al. From a set of seeding and target points, the paths are estimated as the shortest path taking into account a local, directional dependent cost.
The output provided is the connectivity map from each voxel in the volume to the seeding points, plus a vector volume with the directions tangent to the fiber bundles at each point. These directions can be traced back to actually compute the fiber bundles using Finsler Backtracing Module.
The Finsler Tractography Module module uses the fastsweeping algorithm to find the connectivity from a set of seeding points to each voxel in the input DWI volume (or inside the mask, if provided). This connectivity is the minimum cost of arriving at each voxel from the seeds, following the trajectory of the estimated pathways. The cost is computed as the integral along the pathway of a local directional cost computed from the ODF or some other HARDIrelated measurement. A complete description of the algorithm may be found in: J. Melonakos, E. Pichon, S. Angenent, A. Tannenbaum, 'Finsler Active Contours'. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(3):412423. March 2008. A backgroundremoval mask can be used to accelerate computations. Optionally, the algorithm provides at each voxel an estimation of the vector tangent to the optimal pathway at that point (arrival direction). Fastsweeping is full multithreaded, and some other accelerations (checking only those voxels in the causal direction of the solution) have been implemented to obtain a result in a reasonable time. However, an algorithm virtually identical to that in the aforementioned paper may be reproduced fixing the advanced parameters as follows: Cost: (E(q)/Phi(r))^3 Directions: 26 Use threads: deactivate Use accelerated iterations: deactivate (Start accelerated iterations becomes irrelevant).
Use Cases
Create fiber tracks from DWI volume.
Tutorials
N/A
Similar Extensions
N/A
References
 GJ. Melonakos, E. Pichon, S. Angenent, A. Tannenbaum, 'Finsler Active Contours'. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(3):412423. March 2008
Information for Developers
Section under construction. 