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| TRACULA is tool for automatic reconstruction of a set of major white-matter pathways from diffusion-weighted images. It uses global probabilistic tractography with anatomical priors. Prior distributions on the neighboring anatomical structures of each pathway are derived from an atlas and combined with the FreeSurfer cortical parcellation and subcortical segmentation of the subject that is being analyzed to constrain the tractography solutions. This obviates the need for user interaction, ''e.g.,'' to draw ROIs manually or to set thresholds on path angle and length, and thus automates the application of tractography to large datasets. | TRACULA is a tool for automatic reconstruction of a set of major white-matter pathways from diffusion-weighted images. It uses global probabilistic tractography with anatomical priors. Prior distributions on the neighboring anatomical structures of each pathway are derived from an atlas and combined with the FreeSurfer cortical parcellation and subcortical segmentation of the subject that is being analyzed to constrain the tractography solutions. This obviates the need for user interaction, ''e.g.,'' to draw ROIs manually or to set thresholds on path angle and length, and thus automates the application of tractography to large datasets. |
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| The trac-all script is used to preprocess raw diffusion data (correcting for eddy current distortion and B0 field inhomogenities), register them to common spaces, model and reconstruct major white matter pathways (included in the atlas) without any manual intervention. trac-all may be used to execute all the above steps or parts of it depending on the dataset and user's preference for analyzing diffusion data. Alternatively, scripts exist to execute chunks of each processing pipeline, and individual commands may be run to execute a single processing step. To explore all the options in running trac-all please refer to the [[trac-all|trac-all wiki]]. In order to use this script to reconstruct tracts in Diffusion images, all the subjects in the dataset must have Freesurfer Recons. |
All necessary preprocessing of the diffusion-weighted images and reconstruction of pathways is done through the trac-all script (see [[trac-all|trac-all usage]]). is used to preprocess raw diffusion data (correcting for eddy current distortion and B0 field inhomogenities), register them to common spaces, model and reconstruct major white matter pathways (included in the atlas) without any manual intervention. trac-all may be used to execute all the above steps or parts of it depending on the dataset and user's preference for analyzing diffusion data. Alternatively, scripts exist to execute chunks of each processing pipeline, and individual commands may be run to execute a single processing step. Note that, because TRACULA relies on the underlying anatomy as derived from the FreeSurfer [[CorticalParcellation|cortical parcellation]] and [[SubcorticalSegmentation|subcortical segmentation,]] these need to be generated before running trac-all. This means that before running trac-all you will have to analyze your subjects' anatomical images with recon-all and make sure that they have a good-quality mri/aparc+aseg.mgz. |
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| For step by step instruction on how to set up and run TRACULA, please refer to the relevant tutorials from the [[http://surfer.nmr.mgh.harvard.edu/fswiki/CourseDescription|FreeSurfer training workshops:]] | For step by step instruction on how to set up and run TRACULA, please refer to the relevant tutorials from the [[CourseDescription|FreeSurfer training workshops:]] |
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| * [[FsTutorial/TraculaStatistics|Computing Tract Statistics]] | * [[FsTutorial/TraculaStatistics|Computing tract statistics]] |
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| [[http://www.frontiersin.org/Neuroinformatics/10.3389/fninf.2011.00023/abstract|Automated probabilistic reconstruction of white-matter pathways in health and disease using an atlas of the underlying anatomy.]] Yendiki A, Panneck P, Srinivasan P, Stevens A, Zöllei L, Augustinack J, Wang R, Salat D, Ehrlich S, Behrens T, Jbabdi S, Gollub R and Fischl B (2011). Front. Neuroinform. 5:23. doi: 10.3389/fninf.2011.00023 | [[http://www.frontiersin.org/Neuroinformatics/10.3389/fninf.2011.00023/abstract|Automated probabilistic reconstruction of white-matter pathways in health and disease using an atlas of the underlying anatomy.]] Yendiki A, Panneck P, Srinivasan P, Stevens A, Zöllei L, Augustinack J, Wang R, Salat D, Ehrlich S, Behrens T, Jbabdi S, Gollub R and Fischl B (2011). ''Front. Neuroinform.'' 5:23. doi: 10.3389/fninf.2011.00023 |
TRACULA: TRActs Contrained by UnderLying Anatomy
TRACULA is a tool for automatic reconstruction of a set of major white-matter pathways from diffusion-weighted images. It uses global probabilistic tractography with anatomical priors. Prior distributions on the neighboring anatomical structures of each pathway are derived from an atlas and combined with the FreeSurfer cortical parcellation and subcortical segmentation of the subject that is being analyzed to constrain the tractography solutions. This obviates the need for user interaction, e.g., to draw ROIs manually or to set thresholds on path angle and length, and thus automates the application of tractography to large datasets.
Documentation
All necessary preprocessing of the diffusion-weighted images and reconstruction of pathways is done through the trac-all script (see trac-all usage). is used to preprocess raw diffusion data (correcting for eddy current distortion and B0 field inhomogenities), register them to common spaces, model and reconstruct major white matter pathways (included in the atlas) without any manual intervention. trac-all may be used to execute all the above steps or parts of it depending on the dataset and user's preference for analyzing diffusion data. Alternatively, scripts exist to execute chunks of each processing pipeline, and individual commands may be run to execute a single processing step.
Note that, because TRACULA relies on the underlying anatomy as derived from the FreeSurfer cortical parcellation and subcortical segmentation, these need to be generated before running trac-all. This means that before running trac-all you will have to analyze your subjects' anatomical images with recon-all and make sure that they have a good-quality mri/aparc+aseg.mgz.
Tutorials
For step by step instruction on how to set up and run TRACULA, please refer to the relevant tutorials from the FreeSurfer training workshops:
Reference
Automated probabilistic reconstruction of white-matter pathways in health and disease using an atlas of the underlying anatomy. Yendiki A, Panneck P, Srinivasan P, Stevens A, Zöllei L, Augustinack J, Wang R, Salat D, Ehrlich S, Behrens T, Jbabdi S, Gollub R and Fischl B (2011). Front. Neuroinform. 5:23. doi: 10.3389/fninf.2011.00023