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This work is part of the National Alliance for Medical Image Computing (NA-MIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Information on NA-MIC can be obtained from the [http://www.na-mic.org/ NA-MIC website].<br>
 
Author: Yogesh Rathi, Ph.D, Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital<br>
 
  
Contact: Ryan Eckbo, <email>reckbo@bwh.harvard.edu</email><br>
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Contact: <email>slicer-users@bwh.harvard.edu</email><br>
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Website: https://github.com/pnlbwh/ukftractography<br>
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Website: http://slicerdmri.github.io/
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|Image:UKF 1.png|Arcuate fasciculus (AF) tract in the setting of edema [Chen et al, 2015]
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|Image:UKF 2.png|Corpus callosum (CC) tract
 
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We present a framework which uses an unscented Kalman filter for performing
 
tractography. At each point on the fiber the most consistent direction is found
 
as a mixture of previous estimates and of the local model.
 
 
It is very easy to expand the framework and to implement new fiber representations
 
for it. Currently it is possible to tract fibers using two different 1-, 2-, or 3-tensor
 
methods. Both methods use a mixture of Gaussian tensors. One limits the diffusion
 
ellipsoids to a cylindrical shape (the second and third eigenvalue are assumed to be
 
identical) and the other one uses a full tensor representation.
 
 
Authors: Yogesh Rathi (yogesh@bwh.harvard.edu), Stefan Lienhard, Yinpeng Li, Martin
 
Styner, Ipek Oguz, Yundi Shi, Christian Baumgartner (c.f.baumgartner@gmail.com),
 
Ryan Eckbo
 
 
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By default, this module uses a tensor model (either one or two tensors). The default tensor model is a cylinder: both smaller eigenvalues are equal. The NODDI model can also be used.
 
* 1-Tensor tractography
 
* 1-Tensor tractography
 
* 1-Tensor tractography with free water
 
* 1-Tensor tractography with free water
 
* 2-Tensor tractography
 
* 2-Tensor tractography
 
* 2-Tensor tractography with free water
 
* 2-Tensor tractography with free water
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* Neurite orientation dispersion and density imaging (NODDI)
  
  
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Input/Output (IO)
 
 
--dwiFile <std::string> Input DWI Image
 
 
--seedsFile <std::string> Seeds for diffusion. If not specified, full brain tractography will be performed, and the algorithm will start from every voxel in the brain mask where the Generalized Anisotropy is bigger than 0.18
 
 
--labels <std::vector<int>> A vector of the ROI labels to be used (default: 1)
 
 
--maskFile <std::string> Mask for diffusion tractography
 
 
--tracts <std::string> Tracts generated, with first tensor output
 
 
--tractsWithSecondTensor <std::string> Tracts generated with second tensor output (if there is one)
 
 
 
 
Seeding Options
 
 
--seedsPerVoxel <int> Number of seeds per voxel (default: 1)
 
 
--seedFALimit<double> Seed points whose FA are below this value are excluded (default: 0.15)
 
 
 
Model Options
 
 
--numTensor <1|2|3> Number of tensors used (default: 2)
 
 
--fullTensorModel Whether to use the full tensor model. Which models all three eigenvalues seperately, as opposed to lambda2=lambda3.
 
 
--freeWater Adds a term for free water difusion to the model. If checked, the 1T simple model is forced.
 
 
 
Stopping Criteria
 
 
--minFA <double> Abort the tractography when the Fractional Anisotropy is less than this value (default: 0.15)
 
 
--minGA <double> Abort the tractography when the Generalized Anisotropy is less than this value (default: 0.1)
 
 
 
Fiber Scalar Fields
 
 
--recordFA Whether to store FA. Attaches field 'FA', and 'FA2' for 2-tensor case to fiber.
 
 
--recordNMSE Whether to store NMSE. Attaches field 'NMSE' to fiber.
 
 
--recordTrace Whether to store Trace. Attaches field 'Trace', and 'Trace2' for 2-tensor case to fiber.
 
 
--recordFreeWater Whether to store the fraction of free water. Attaches field 'FreeWater' to fiber.
 
 
--recordState Whether to attach the states to the fiber. Will generate field 'state'.
 
 
--recordCovariance Whether to store the covariance. Will generate field 'covariance' in fiber.
 
 
--recordTensors Recording the tensors enables Slicer to color the fiber bundles by FA, orientation, and so on. The fields will be called 'TensorN', where N is the tensor number.
 
 
 
Advanced Options
 
 
--numThreads <int> Number of threads used during compuation. Set to the number of cores on your workstation for optimal speed. If left undefined boost will figure out the number of cores, and hence threads, during runtime.
 
 
--normalizedDWIData Whether the DWI input data is already normalized
 
 
--weightsOnTensors <std::vector<double>> Weights on different tensors when using multiple tensors. There must be one weight for each tensor, and the weights must sum up to 1. Defaults to equally weighted.
 
 
--maxHalfFiberLength <double> The max length limit of the half fibers generated during tractography. Here the fiber is "half" because the tractography goes in only one direction from one seed point at a time (default: 10000)
 
 
--Qm <double> Process noise for angles/direction (Will be set during runtime to the optimal value for the chosen model, unless overriden by user).
 
 
--Ql <double> Process noise for eigenvalues (Will be set during runtime to the optimal value for the chosen model, unless overriden by user).
 
 
--Qw <double> Process noise for free water weights, ignored if no free water estimation (Will be set during runtime to the optimal value for the chosen model, unless overriden by user).
 
 
--Rs <double> Measurement noise (Will be set during runtime to the optimal value for the chosen model, unless overriden by user).
 
 
--stepLength <double> Step length i.e. size of the step taken in the most consistent direction during each iteration of tractography given in millimeters (Will be set during runtime to the optimal value for the chosen model, unless overriden by user).
 
 
--maxBranchingAngle <double> Maximum branching angle, in degrees. When using multiple tensors, a new branch will be created when the tensors' major directions form an angle between
 
(minBranchingAngle, maxBranchingAngle). Branching is supressed when this maxBranchingAngle is set to 0.0
 
 
--minBranchingAngle <double> Minimum branching angle, in degrees. When using multiple tensors, a new branch will be created when the tensors' major directions form an angle between (minBranchingAngle, maxBranchingAngle)
 
 
 
Additional Output Options
 
 
--noTransformPosition Don't transform Points back from ijk->RAS when writing the output fiber
 
 
--branchesOnly Only output branches, ignore the primary tracts
 
 
--storeGlyphs Store tensors' main directions as two-point lines in a separate file named glyphs_{tracts}. When using multiple tensors, only the major tensors' main directions are stored
 
 
--outputNormalizedDWIData Whether to output the DWI after normalization (i.e. preprocessing)
 
 
 
Tractography unrelated options
 
 
--returnparameterfile <std::string> Filename in which to write simple return parameters (int, float, int-vector, etc.) as opposed to bulk return parameters (image, geometry, transform, measurement, table).
 
 
--processinformationaddress <std::string> Address of a structure to store process information (progress, abort, etc.). (default: 0)
 
 
--xml Produce xml description of command line arguments.
 
 
--echo Echo the command line arguments.
 
 
--, --ignore_rest Ignores the rest of the labeled arguments following this flag.
 
 
--version Displays version information and exits.
 
 
-h, --help Displays usage information and exits.
 
 
 
 
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* Tractography Seeding
 
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* Tractography ROI Seeding
 
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Reference for 2-tensor tractography:
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* Reference for 2-tensor tractography:  
* http://pnl.bwh.harvard.edu/pub/papers_html/MalcolmIEEETransMed10.html
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** Malcolm, J.G., Shenton, M.E. and Rathi, Y., 2010. [http://www.ncbi.nlm.nih.gov/pubmed/20805043 Filtered multitensor tractography. IEEE transactions on medical imaging, 29(9), pp.1664-1675].
 
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* Reference for 1-tensor and 2-tensor + free-water:  
Reference for 1-tensor and 2-tensor + free-water:
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** Baumgartner C, Michailovich O, Levitt J, Pasternak O, Bouix S, Westin C, Rathi Y. [http://cmic.cs.ucl.ac.uk/cdmri12/pdfs/o1_3.pdf A unified tractography framework for comparing diffusion models on clinical scans. In Computational Diffusion MRI Workshop of MICCAI, Nice 2012 (pp. 27-32).]
* C. Baumgartner, O. Michailovich, O. Pasternak, S. Bouix, J. Levitt, ME Shenton, C-F Westin, Y. Rathi,
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* Reference for using UKF in clinical imaging data from tumor patients with edema:  
"A unified tractography framework for comparing diffusion models on clinical scans": in Workshop
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** Chen Z, Tie Y, Olubiyi O, Rigolo L, Mehrtash A, Norton I, Pasternak O, Rathi Y, Golby AJ, O'Donnell LJ. [http://www.ncbi.nlm.nih.gov/pubmed/26082890 Reconstruction of the arcuate fasciculus for surgical planning in the setting of peritumoral edema using two-tensor unscented Kalman filter tractography. NeuroImage: Clinical. 2015 Dec 31;7:815-22].
on computational diffusion MRI, 2012.
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* Reference for NODDI UKF tractography:
 
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** Reddy, C.P. and Rathi, Y., 2016. [http://www.ncbi.nlm.nih.gov/pubmed/27147956 Joint Multi-Fiber NODDI Parameter Estimation and Tractography Using the Unscented Information Filter. Frontiers in Neuroscience, 10].
 
 
  
  
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* https://github.com/pnlbwh/ukftractography
 
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* https://www.nitrc.org/projects/ukftractography
  
 
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Latest revision as of 13:19, 27 November 2019

Home < Documentation < Nightly < Modules < UKFTractography


For the latest Slicer documentation, visit the read-the-docs.


Introduction and Acknowledgements


Title: UKF Tractography
Author(s)/Contributor(s): Yogesh Rathi, Stefan Lienhard, Yinpeng Li, Martin Styner, Ipek Oguz, Yundi Shi, Christian Baumgartner, Kent Williams, Hans Johnson, Peter Savadjiev, Carl-Fredrik Westin, Lauren O'Donnell, Jessica Lee.
License:
Acknowledgements: The development of this module was supported by NIH grants R01 MH097979 (PI Rathi), R01 MH092862 (PIs Westin and Verma), U01 NS083223 (PI Westin), R01 MH074794 (PI Westin) and P41 EB015902 (PI Kikinis), U01 CA199459 (PI O'Donnell), and P41 EB015898 (NCIGT).


Contact: <email>slicer-users@bwh.harvard.edu</email>
Website: https://github.com/pnlbwh/ukftractography
Website: http://slicerdmri.github.io/


SlicerDMRI  
NAC  
Arcuate fasciculus (AF) tract in the setting of edema [Chen et al, 2015]  
Corpus callosum (CC) tract  

Module Description

This module traces fibers in a DWI Volume using the multiple tensor unscented Kalman Filter methodology. At each point on the fiber the most consistent direction is found as a mixture of previous estimates and of the local model.

For more information, please reference: Malcolm, James G., Martha E. Shenton, and Yogesh Rathi. "Filtered multitensor tractography." Medical Imaging, IEEE Transactions on 29.9 (2010): 1664-1675. (http://www.ncbi.nlm.nih.gov/pubmed/20805043)


For additional references, please see below (References section).

Use Cases

By default, this module uses a tensor model (either one or two tensors). The default tensor model is a cylinder: both smaller eigenvalues are equal. The NODDI model can also be used.

  • 1-Tensor tractography
  • 1-Tensor tractography with free water
  • 2-Tensor tractography
  • 2-Tensor tractography with free water
  • Neurite orientation dispersion and density imaging (NODDI)




Tutorials

Panels and their use

Parameters:

  • IO: Input/output parameters
    • Input DWI Volume (dwiFile): Input diffusion weighted (DWI) volume
    • Input Label Map (seedsFile): Seeds for diffusion. If not specified, full brain tractography will be performed, and the algorithm will start from every voxel in the brain mask where the Generalized Anisotropy is bigger than 0.18
    • ROI label to use for seeding (labels): A vector of the ROI labels to be used. There are the voxel values where tractography should be seeded.
    • Input brain mask (maskFile): Brain mask for diffusion tractography. Tracking will only be performed inside this mask.
    • Output Fiber Bundle (tracts): Output fiber tracts.
  • Tractography Options: Basic Parameters
    • Seeding: Number of seeds per voxel (seedsPerVoxel): Tractography parameter used in all models. Each seed generates a fiber, thus using more seeds generates more fibers. In general use 1 or 2 seeds, and for a more thorough result use 5 or 10 (depending on your machine this may take up to 2 days to run). Default: 1. Range: 0-50.
    • Seeding: Minimum seed FA (seedingThreshold): Tractography parameter used in all models. Seed points whose fractional anisotropy (FA) or mean signal are below this value are excluded. Default: 0.18. Range: 0-1.
    • Stopping Criterion: Terminating FA (stoppingFA): Tractography parameter used in tensor model. Tractography will stop when the fractional anisotropy (FA) of the tensor being tracked is less than this value. Note: make sure to also decrease the GA to track through lower anisotropy areas. This parameter is used only in tensor models. Default: 0.15. Range: 0-1.
    • Stopping Criterion: Terminating mean signal (stoppingThreshold): Tractography parameter used in all models. Tractography will stop when the mean signal is below this value. Default: 0.1. Range: 0-1.
    • Tracking: Number of threads (numThreads): Tractography parameter used in all models. Number of threads used during computation. Set to the number of cores on your workstation for optimal speed. If left undefined, the number of cores detected will be used.
    • Tracking: Number of tensors/orientations in model (numTensor): Number of tensors (tensor model) or orientations (NODDI model) used
    • Tracking: Step length of tractography (in mm) (stepLength): Tractography parameter used in all models. Step size when conducting tractography. Default: 0.3. Range: 0.1-1.
    • Tracking: Rate of change of tensor direction/orientation (Qm): UKF data fitting parameter for tensor or NODDI model: Process noise for angles/direction. Defaults: Noddi-0.001; Single tensor-0.005; other-0.001. Suggested Range: 0.00001 - 0.25. Default of 0.0 indicates the program will assign value based on other model parameters.
    • Output: Step length of output tractography (in mm) (recordLength): Tractography parameter used in all models. Step size between points saved along fibers. Default: 0.9. Range: 0.1-4.
    • Output: Maximum tract length (in mm) (maxHalfFiberLength): Tractography parameter used in all models. The max length limit of the half fibers generated during tractography. A fiber is "half" when the tractography goes in only one direction from one seed point at a time. Default: 250 mm. Range: 1-500 mm.
    • Output: Save Normalized Mean Square Error (recordNMSE): Record output from data fitting: Store normalized mean square error (NMSE) along fibers.
  • Tensor Model (default): Tensor model parameters
    • Tensor Model: Estimate term for free water (freeWater): Adds a term for free water diffusion to the model. The free water model is a tensor with all 3 eigenvalues equal to the diffusivity of free water (0.003). To output the free water fraction, make sure to use the "save free water" parameter.
    • Output: Save tensor FA (recordFA): Record output from tensor model: Save fractional anisotropy (FA) of the tensor(s). Attaches field 'FA' or 'FA1' and 'FA2' for 2-tensor case to fiber.
    • Output: Save tensor trace (recordTrace): Record output from tensor model: Save the trace of the tensor(s). Attaches field 'Trace' or 'Trace1' and 'Trace2' for 2-tensor case to fiber.
    • Output: Save free water fraction (recordFreeWater): Record output from tensor plus free water model: Save the fraction of free water. Attaches field 'FreeWater' to fiber.
    • Output: Save tensors (recordTensors): Record output from tensor model: Save the tensors that were computed during tractography (if using tensor model). The fields will be called 'TensorN', where N is the tensor number. Recording the tensors enables Slicer to color the fiber bundles by FA, orientation, and so on. Recording the tensors also enables quantitative analyses.
    • UKF Parameter (Advanced): Rate of change of eigenvalues (Ql): UKF data fitting parameter for tensor model: Process noise for eigenvalues. Defaults: 1 tensor-300 ; 2 tensor-50 ; 3 tensor-100. Suggested Range: 1-1000. Default of 0.0 indicates the program will assign value based on other model parameters.
    • UKF Parameter (Advanced): Rate of change of freewater weight (Qw): UKF data fitting parameter for tensor plus free water model: Process noise for free water weights, ignored if no free water estimation. Defaults: 1 tensor-0.0025; 2 tensor-0.0015. Suggested Range: 0.00001-0.25. Default of 0.0 indicates the program will assign value based on other model parameters.
  • NODDI Model: Use NODDI model
    • NODDI Model: Use NODDI Model (noddi): Use neurite orientation dispersion and density imaging (NODDI) model instead of tensor model.
    • Output: Save NODDI intra-cellular volume fraction. (recordVic): Record output from NODDI model: Store volume fraction of intra-cellular compartment along fibers.
    • Output: Save NODDI dispersion parameter (kappa) (recordKappa): Record output from NODDI model: concentration parameter that measures the extent of orientation dispersion.
    • Output: Save NODDI CSF volume fraction. (recordViso): Record output from NODDI model: Store volume fraction of CSF compartment along fibers.
    • UKF Parameter (Advanced): Rate of change of kappa value (Qkappa): UKF data fitting parameter for NODDI model: Rate of change of kappa (orientation dispersion) value. Higher kappa values indicate more fiber dispersion. Default: 0.01.
    • UKF Parameter (Advanced): Rate of change of intracellular volume fraction (Qvic): UKF data fitting parameter for NODDI model: Rate of change of volume fraction of intracellular component. Default: 0.004.
  • Signal Parameters (Expert Only):
    • Signal Parameter (Advanced): Expected noise in signal (Rs): UKF Data Term: Measures expected noise in signal. This is used by the UKF method to decide how much to trust the data. This should be increased for very noisy data or reduced for high quality data. Defaults: single tensor/orientation-0.01; other-0.02. Suggested Range: 0.001-0.25. Default of 0.0 indicates the program will assign value based on other model parameters.
  • Not Used: Debug/Develop Only :
    • Signal Parameter (Advanced): Sigma for Gaussian interpolation of signal (sigmaSignal): UKF Data Term: Sigma for Gaussian kernel used to interpolate the signal at sub-voxel locations. Default: 0.0
    • Record states (recordState): Develop/Debug Only: Store the states along the fiber. Will generate field 'state'. The state is the model for UKF. In the case of the two tensor model, it is a ten-parameter vector.
    • Record the covariance matrix (recordCovariance): Develop/Debug Only: Store the covariance matrix along the fiber. Will generate field 'covariance' in fiber. This is the covariance from the unscented Kalman filter.
    • Use full tensor model (fullTensorModel): Develop/Debug Only: Use the full tensor model instead of the default model. The default model has both smaller eigenvalues equal, whereas the full model allows 3 different eigenvalues.
    • Maximum branching angle (maxBranchingAngle): Develop/Debug Only: Maximum branching angle, in degrees. When using multiple tensors, a new branch will be created when the tensors' major directions form an angle between (minBranchingAngle, maxBranchingAngle). Branching is supressed when this maxBranchingAngle is set to 0.0. Default: 0.0. Range: 0-90.
    • Minimum branching angle (minBranchingAngle): Develop/Debug Only: Minimum branching angle, in degrees. When using multiple tensors, a new branch will be created when the tensors' major directions form an angle between (minBranchingAngle, maxBranchingAngle). Default: 0. Range: 0-90.
    • Branched Fibers (second tensor, optional) (tractsWithSecondTensor): Develop/Debug Only: Tracts generated, with second tensor output (if there is one)
    • Store tensors' main directions (storeGlyphs): Develop/Debug Only: Store tensors' main directions as two-point lines in a separate file named glyphs_{tracts}. When using multiple tensors, only the major tensors' main directions are stored
    • Write Binary Tracts File (writeAsciiTracts): Develop/Debug Only: Write tract file as ASCII text format. Default is not ASCII. Default tracts are written on VTK binary data file.
    • Write uncompressed Tracts File (writeUncompressedTracts): Develop/Debug Only: Write tract file as a VTK uncompressed data file
    • DEPRECATED REMOVED: minGA (was Stopping Criterion: Terminating GA):
       DEPRECATED REMOVED: this parameter is no longer valid! Please use 'stoppingThreshold' instead! GA is no longer used as a stopping threshold. Please see https://github.com/pnlbwh/ukftractography/pull/64 for more information. (Was: Tractography parameter used in all models. Tractography will stop when the generalized anisotropy (GA) is less than this value. GA is a normalized variance of the input signals (so it does not depend on any model). Note: to extend tracking through low anisotropy areas, this parameter is often more effective than the minFA. This parameter is used by both tensor and NODDI models. Default: 0.1. Range: 0-1.)
     
    • Allow in-memory data transfer (AllowMemoryTransfer): Allow in-memory data transfer


List of parameters generated transforming this XML file using this XSL file. To update the URL of the XML file, edit this page.


Similar Modules

  • Tractography Seeding
  • Tractography ROI Seeding
  • Diffusion Tensor Estimation

References



Information for Developers