Fiber assignment by continuous tracking algorithm (FACT)
Updates to Article Attributes
It is the most commonFiber assignment by continuous tracking (FACT) algorithms are a commonly used deterministic post-processing algorithmalgorithms for magnetic resonance tractography studies (FACT, Fiber Assignment by Continuous Tracking).
TheIn these algorithms axonal fiber bundle isbundles are reconstructed - voxel by voxel - following the direction of the main eigenvector. The characteristicbeginning of this particular algorithm, totally based on data, is the remarkable computational speed.
The beginning of the reconstruction process can take place in different ways:
- from a single voxel (seed point);
- from several independent voxels;
- from several voxels belonging to the same ROI (Region Of Interest).
The characteristic of this particular type of algorithm, totally based on data, is the remarkably fast computational speed. Therefore, although FACT algorithms create some predictable errors, they may in some cases be preferred to more accurate algorithms 2,3.
-<p>It is the most common post-processing algorithm for magnetic resonance tractography studies (FACT, Fiber Assignment by Continuous Tracking).</p><p>The fiber bundle is reconstructed - voxel by voxel - following the direction of the main eigenvector. The characteristic of this particular algorithm, totally based on data, is the remarkable computational speed.</p><p>The beginning of the reconstruction process can take place in different ways:</p><ul>- +<p><strong>Fiber assignment by continuous tracking</strong> (FACT) algorithms are a commonly used deterministic post-processing algorithms for <a title="Diffusion tensor imaging and fiber tractography" href="/articles/diffusion-tensor-imaging-and-fiber-tractography">magnetic resonance tractography</a> studies .</p><p>In these algorithms axonal fiber bundles are reconstructed - voxel by voxel - following the direction of the main eigenvector. The beginning of this reconstruction process can take place in different ways:</p><ul>
-</ul><p><!--[if gte mso 9]><xml>- +</ul><p>The characteristic of this particular type of algorithm, totally based on data, is the remarkably fast computational speed. Therefore, although FACT algorithms create some predictable errors, they may in some cases be preferred to more accurate algorithms <sup>2,3</sup>.</p><p> </p><p><!--[if gte mso 9]><xml>
References changed:
- 1. Jiang H, van Zijl PC, Kim J, Pearlson GD, Mori S. DtiStudio: resource program for diffusion tensor computation and fiber bundle tracking. (2006) Computer methods and programs in biomedicine. 81 (2): 106-16. <a href="https://doi.org/10.1016/j.cmpb.2005.08.004">doi:10.1016/j.cmpb.2005.08.004</a> - <a href="https://www.ncbi.nlm.nih.gov/pubmed/16413083">Pubmed</a> <span class="ref_v4"></span>
- 2. C. Anastasopoulos, M. Reisert, V.G. Kiselev, T. Nguyen-Thanh, A. Schulze-Bonhage, J. Zentner, I. Mader. Local and Global Fiber Tractography in Patients with Epilepsy. (2014) American Journal of Neuroradiology. 35 (2): 291. <a href="https://doi.org/10.3174/ajnr.A3752">doi:10.3174/ajnr.A3752</a> - <a href="https://www.ncbi.nlm.nih.gov/pubmed/24157735">Pubmed</a> <span class="ref_v4"></span>
- 3. Theoretical analysis of the effects of noise on diffusion tensor imaging. (2001) Magnetic Resonance in Medicine. 46 (6): 1174. <a href="https://doi.org/10.1002/mrm.1315">doi:10.1002/mrm.1315</a> - <a href="https://www.ncbi.nlm.nih.gov/pubmed/11746585">Pubmed</a> <span class="ref_v4"></span>
- 1. Jiang H, van Zijl PC, Kim J, Pearlson GD, Mori S.:"DtiStudio: resource program for diffusion tensor computation and fiber bundle tracking.". Comput Methods Programs Biomed. 2006 Feb;81(2):106-16. Epub 2006 Jan 18. DOI: 10.1016/j.cmpb.2005.08.004