Estimate fibre orientation distributions from diffusion data using spherical deconvolution
dwi2fod [ options ] algorithm dwi response odf [ response odf ... ]
- algorithm: the algorithm to use for FOD estimation. (options are: csd,msmt_csd)
- dwi: the input diffusion-weighted image
- response odf: pairs of input tissue response and output ODF images
The spherical harmonic coefficients are stored according the conventions described the main documentation, which can be found at the following link:
Perform single-shell single-tissue CSD:
$ dwi2fod csd dwi.mif response_wm.txt wmfod.mif
This algorithm is designed for single-shell data and only uses a single b-value. The response function text file provided should only contain a a single row, corresponding to the b-value used for CSD.
Perform multi-shell multi-tissue CSD:
$ dwi2fod msmt_csd dwi.mif response_wm.txt wmfod.mif response_gm.txt gm.mif response_csf.txt csf.mif
This example is the most common use case of multi-tissue CSD, estimating a white matter FOD, and grey matter and CSF compartments. This algorithm requires at least three unique b-values to estimate three tissue compartments. Each response function text file should have a number of rows equal to the number of b-values used. If only two unique b-values are available, it’s also possible to estimate only two tissue compartments, e.g., white matter and CSF.
DW gradient table import options¶
- -grad file Provide the diffusion-weighted gradient scheme used in the acquisition in a text file. This should be supplied as a 4xN text file with each line is in the format [ X Y Z b ], where [ X Y Z ] describe the direction of the applied gradient, and b gives the b-value in units of s/mm^2. If a diffusion gradient scheme is present in the input image header, the data provided with this option will be instead used.
- -fslgrad bvecs bvals Provide the diffusion-weighted gradient scheme used in the acquisition in FSL bvecs/bvals format files. If a diffusion gradient scheme is present in the input image header, the data provided with this option will be instead used.
DW shell selection options¶
- -shells b-values specify one or more b-values to use during processing, as a comma-separated list of the desired approximate b-values (b-values are clustered to allow for small deviations). Note that some commands are incompatible with multiple b-values, and will report an error if more than one b-value is provided.
WARNING: note that, even though the b=0 volumes are never referred to as shells in the literature, they still have to be explicitly included in the list of b-values as provided to the -shell option! Several algorithms which include the b=0 volumes in their computations may otherwise return an undesired result.
Options common to more than one algorithm¶
- -directions file specify the directions over which to apply the non-negativity constraint (by default, the built-in 300 direction set is used). These should be supplied as a text file containing [ az el ] pairs for the directions.
- -lmax order the maximum spherical harmonic order for the output FOD(s).For algorithms with multiple outputs, this should be provided as a comma-separated list of integers, one for each output image; for single-output algorithms, only a single integer should be provided. If omitted, the command will use the lmax of the corresponding response function (i.e based on its number of coefficients), up to a maximum of 8.
- -mask image only perform computation within the specified binary brain mask image.
Options for the Constrained Spherical Deconvolution algorithm¶
- -filter spec the linear frequency filtering parameters used for the initial linear spherical deconvolution step (default = [ 1 1 1 0 0 ]). These should be supplied as a text file containing the filtering coefficients for each even harmonic order.
- -neg_lambda value the regularisation parameter lambda that controls the strength of the non-negativity constraint (default = 1).
- -norm_lambda value the regularisation parameter lambda that controls the strength of the constraint on the norm of the solution (default = 1).
- -threshold value the threshold below which the amplitude of the FOD is assumed to be zero, expressed as an absolute amplitude (default = 0).
- -niter number the maximum number of iterations to perform for each voxel (default = 50). Use ‘-niter 0’ for a linear unconstrained spherical deconvolution.
Options for the Multi-Shell, Multi-Tissue Constrained Spherical Deconvolution algorithm¶
- -norm_lambda value the regularisation parameter lambda that controls the strength of the constraint on the norm of the solution (default = 1e-10).
- -neg_lambda value the regularisation parameter lambda that controls the strength of the non-negativity constraint (default = 1e-10).
- -predicted_signal image output the predicted dwi image.
- -strides spec specify the strides of the output data in memory; either as a comma-separated list of (signed) integers, or as a template image from which the strides shall be extracted and used. The actual strides produced will depend on whether the output image format can support it.
- -info display information messages.
- -quiet do not display information messages or progress status; alternatively, this can be achieved by setting the MRTRIX_QUIET environment variable to a non-empty string.
- -debug display debugging messages.
- -force force overwrite of output files (caution: using the same file as input and output might cause unexpected behaviour).
- -nthreads number use this number of threads in multi-threaded applications (set to 0 to disable multi-threading).
- -config key value (multiple uses permitted) temporarily set the value of an MRtrix config file entry.
- -help display this information page and exit.
- -version display version information and exit.
- If using csd algorithm:
Tournier, J.-D.; Calamante, F. & Connelly, A. Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution. NeuroImage, 2007, 35, 1459-1472
- If using msmt_csd algorithm:
Jeurissen, B; Tournier, J-D; Dhollander, T; Connelly, A & Sijbers, J. Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data. NeuroImage, 2014, 103, 411-426
Tournier, J.-D.; Calamante, F., Gadian, D.G. & Connelly, A. Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution. NeuroImage, 2004, 23, 1176-1185
Tournier, J.-D.; Smith, R. E.; Raffelt, D.; Tabbara, R.; Dhollander, T.; Pietsch, M.; Christiaens, D.; Jeurissen, B.; Yeh, C.-H. & Connelly, A. MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. NeuroImage, 2019, 202, 116137
Copyright: Copyright (c) 2008-2023 the MRtrix3 contributors.
This Source Code Form is subject to the terms of the Mozilla Public License, v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
Covered Software is provided under this License on an “as is” basis, without warranty of any kind, either expressed, implied, or statutory, including, without limitation, warranties that the Covered Software is free of defects, merchantable, fit for a particular purpose or non-infringing. See the Mozilla Public License v. 2.0 for more details.
For more details, see http://www.mrtrix.org/.