List of MRtrix3 commands

Lang Command Synopsis
C++ 5tt2gmwmi Generate a mask image appropriate for seeding streamlines on the grey matter-white matter interface
C++ 5tt2vis Generate an image for visualisation purposes from an ACT 5TT segmented anatomical image
C++ 5ttcheck Thoroughly check that one or more images conform to the expected ACT five-tissue-type (5TT) format
C++ 5ttedit Manually set the partial volume fractions in an ACT five-tissue-type (5TT) image using mask images
Python 5ttgen Generate a 5TT image suitable for ACT
C++ afdconnectivity Obtain an estimate of fibre connectivity between two regions using AFD and streamlines tractography
C++ amp2response Estimate response function coefficients based on the DWI signal in single-fibre voxels
C++ amp2sh Convert a set of amplitudes (defined along a set of corresponding directions) to their spherical harmonic representation
C++ connectome2tck Extract streamlines from a tractogram based on their assignment to parcellated nodes
C++ connectomestats Connectome group-wise statistics at the edge level using non-parametric permutation testing
C++ dcmedit Edit DICOM file in-place
C++ dcminfo Output DICOM fields in human-readable format
C++ dirflip Invert the polarity of individual directions so as to optimise a unipolar electrostatic repulsion model
C++ dirgen Generate a set of uniformly distributed directions using a bipolar electrostatic repulsion model
C++ dirmerge Splice / merge multiple sets of directions in such a way as to maintain near-optimality upon truncation
C++ dirorder Reorder a set of directions to ensure near-uniformity upon truncation
C++ dirsplit Split a set of evenly distributed directions (as generated by dirgen) into approximately uniformly distributed subsets
C++ dirstat Report statistics on a direction set
C++ dwi2adc Convert mean dwi (trace-weighted) images to mean ADC maps
C++ dwi2fod Estimate fibre orientation distributions from diffusion data using spherical deconvolution
C++ dwi2mask Generates a whole brain mask from a DWI image
Python dwi2response Estimate response function(s) for spherical deconvolution
C++ dwi2tensor Diffusion (kurtosis) tensor estimation
Python dwibiascorrect Perform B1 field inhomogeneity correction for a DWI volume series
Python dwicat Concatenating multiple DWI series accounting for differential intensity scaling
C++ dwidenoise dMRI noise level estimation and denoising using Marchenko-Pastur PCA
C++ dwiextract Extract diffusion-weighted volumes, b=0 volumes, or certain shells from a DWI dataset
Python dwifslpreproc Perform diffusion image pre-processing using FSL’s eddy tool; including inhomogeneity distortion correction using FSL’s topup tool if possible
Python dwigradcheck Check the orientation of the diffusion gradient table
Python dwinormalise Perform various forms of intensity normalisation of DWIs
Python dwishellmath Apply an mrmath operation to each b-value shell in a DWI series
C++ fixel2sh Convert a fixel-based sparse-data image into an spherical harmonic image
C++ fixel2tsf Map fixel values to a track scalar file based on an input tractogram
C++ fixel2voxel Convert a fixel-based sparse-data image into some form of scalar image
C++ fixelcfestats Fixel-based analysis using connectivity-based fixel enhancement and non-parametric permutation testing
C++ fixelconnectivity Generate a fixel-fixel connectivity matrix
C++ fixelconvert Convert between the old format fixel image (.msf / .msh) and the new fixel directory format
C++ fixelcorrespondence Obtain fixel-fixel correpondence between a subject fixel image and a template fixel mask
C++ fixelcrop Crop/remove fixels from sparse fixel image using a binary fixel mask
C++ fixelfilter Perform filtering operations on fixel-based data
C++ fixelreorient Reorient fixel directions
C++ fod2dec Generate FOD-based DEC maps, with optional panchromatic sharpening and/or luminance/perception correction
C++ fod2fixel Perform segmentation of continuous Fibre Orientation Distributions (FODs) to produce discrete fixels
Python foreach Perform some arbitrary processing step for each of a set of inputs
C++ label2colour Convert a parcellated image (where values are node indices) into a colour image
C++ label2mesh Generate meshes from a label image
C++ labelconvert Convert a connectome node image from one lookup table to another
Python labelsgmfix In a FreeSurfer parcellation image, replace the sub-cortical grey matter structure delineations using FSL FIRST
C++ maskdump Print out the locations of all non-zero voxels in a mask image
C++ maskfilter Perform filtering operations on 3D / 4D mask images
C++ mesh2voxel Convert a mesh surface to a partial volume estimation image
C++ meshconvert Convert meshes between different formats, and apply transformations
C++ meshfilter Apply filter operations to meshes
C++ mraverageheader Calculate the average (unbiased) coordinate space of all input images
C++ mrcalc Apply generic voxel-wise mathematical operations to images
C++ mrcat Concatenate several images into one
C++ mrcheckerboardmask Create bitwise checkerboard image
C++ mrclusterstats Voxel-based analysis using permutation testing and threshold-free cluster enhancement
C++ mrcolour Apply a colour map to an image
C++ mrconvert Perform conversion between different file types and optionally extract a subset of the input image
C++ mrdegibbs Remove Gibbs Ringing Artifacts
C++ mrdump Print out the values within an image
C++ mredit Directly edit the intensities within an image from the command-line
C++ mrfilter Perform filtering operations on 3D / 4D MR images
C++ mrgrid Modify the grid of an image without interpolation (cropping or padding) or by regridding to an image grid with modified orientation, location and or resolution. The image content remains in place in real world coordinates.
C++ mrhistmatch Modify the intensities of one image to match the histogram of another
C++ mrhistogram Generate a histogram of image intensities
C++ mrinfo Display image header information, or extract specific information from the header
C++ mrmath Compute summary statistic on image intensities either across images, or along a specified axis of a single image
C++ mrmetric Computes a dissimilarity metric between two images
C++ mrregister Register two images together using a symmetric rigid, affine or non-linear transformation model
C++ mrstats Compute images statistics
C++ mrthreshold Create bitwise image by thresholding image intensity
C++ mrtransform Apply spatial transformations to an image
C++ mrview The MRtrix image viewer
C++ mtnormalise Multi-tissue informed log-domain intensity normalisation
C++ peaks2amp Extract amplitudes from a peak directions image
Python population_template Generates an unbiased group-average template from a series of images
Python responsemean Calculate the mean response function from a set of text files
C++ sh2amp Evaluate the amplitude of an image of spherical harmonic functions along specified directions
C++ sh2peaks Extract the peaks of a spherical harmonic function in each voxel
C++ sh2power Compute the total power of a spherical harmonics image
C++ sh2response Generate an appropriate response function from the image data for spherical deconvolution
C++ shbasis Examine the values in spherical harmonic images to estimate (and optionally change) the SH basis used
C++ shconv Perform a spherical convolution
C++ shview View spherical harmonics surface plots
C++ tck2connectome Generate a connectome matrix from a streamlines file and a node parcellation image
C++ tck2fixel Compute a fixel TDI map from a tractogram
C++ tckconvert Convert between different track file formats
C++ tckdfc Perform the Track-Weighted Dynamic Functional Connectivity (TW-dFC) method
C++ tckedit Perform various editing operations on track files
C++ tckgen Perform streamlines tractography
C++ tckglobal Multi-Shell Multi-Tissue Global Tractography
C++ tckinfo Print out information about a track file
C++ tckmap Use track data as a form of contrast for producing a high-resolution image
C++ tckresample Resample each streamline in a track file to a new set of vertices
C++ tcksample Sample values of an associated image along tracks
C++ tcksift Filter a whole-brain fibre-tracking data set such that the streamline densities match the FOD lobe integrals
C++ tcksift2 Optimise per-streamline cross-section multipliers to match a whole-brain tractogram to fixel-wise fibre densities
C++ tckstats Calculate statistics on streamlines lengths
C++ tcktransform Apply a spatial transformation to a tracks file
C++ tensor2metric Generate maps of tensor-derived parameters
C++ transformcalc Perform calculations on linear transformation matrices
C++ transformcompose Compose any number of linear transformations and/or warps into a single transformation
C++ transformconvert Convert linear transformation matrices
C++ tsfdivide Divide corresponding values in track scalar files
C++ tsfinfo Print out information about a track scalar file
C++ tsfmult Multiply corresponding values in track scalar files
C++ tsfsmooth Gaussian filter a track scalar file
C++ tsfthreshold Threshold and invert track scalar files
C++ tsfvalidate Validate a track scalar file against the corresponding track data
C++ vectorstats Statistical testing of vector data using non-parametric permutation testing
C++ voxel2fixel Map the scalar value in each voxel to all fixels within that voxel
C++ voxel2mesh Generate a surface mesh representation from a voxel image
C++ warp2metric Compute fixel-wise or voxel-wise metrics from a 4D deformation field
C++ warpconvert Convert between different representations of a non-linear warp
C++ warpcorrect Replaces voxels in a deformation field that point to a specific out of bounds location with nan,nan,nan
C++ warpinit Create an initial warp image, representing an identity transformation
C++ warpinvert Invert a non-linear warp field