Command Line Interface

DECAES provides a command line interface (CLI) for calling the main analysis functions: T2mapSEcorr for computing $T_2$-distributions, and T2partSEcorr for running $T_2$-parts analysis on the resulting $T_2$-distributions for computing measures such as the myelin water fraction.

Using the CLI

Assuming you have DECAES installed, there are two equivalent ways to use the CLI:

1. Helper script: Create a simple Julia script which calls the entrypoint function main provided by this package. For example, save the following code in a Julia script called decaes.jl (or, download the script located here):

using DECAES # load the package
main() # call command line interface

An image file image.nii can be passed to DECAES by running this script with julia from the command line:

$ julia decaes.jl -- image.nii <COMMAND LINE ARGS>

2. Julia -e flag: The contents of the above script can equivalently be passed directly to julia using the -e (for "evaluate") flag:

$ julia -e 'using DECAES; main()' -- image.nii <COMMAND LINE ARGS>

Either way of calling the CLI forwards the arguments <COMMAND LINE ARGS> to the entrypoint function main. Available command line arguments are detailed in the Arguments section.

For the remainder of this section, we will make use of the decaes.jl script from option 1.

File types

Input files must be one of the following file types:

  1. NIfTI file with extension .nii, or gzip compressed NIfTI file with extension .nii.gz. See NIfTI.jl for more information.
  2. MATLAB file with extension .mat. Note: .mat files saved in the oldest format v4 are not supported, but all newer formats (v6, v7, and v7.3) are supported. See MAT.jl for more information.
  3. Philips PAR/REC file pair with extensions .par and .rec (or .PAR and .REC).
  4. Philips XML/REC file pair with extensions .xml and .rec (or .XML and .REC).

All output files are saved as .mat files in format v7.3.


If your data is in DICOM format, the freely available dcm2niix tool is able to convert DICOM files into NIfTI format

  • Input files are interpreted as 4D arrays (or 3D arrays for mask files) when loaded; ensure that the underlying data is stored with the first three dimensions as (row, column, slice), and the last dimension as echo (or $T_2$ bin, or omitted for mask files)
  • Images read from NIfTI and PAR/XML/REC files are coerced into the appropriate dimension; errors or unexpected behaviour may occur if the data is not stored with the correct dimensions
  • MATLAB files are searched for arrays with the appropriate dimension; the first such array that is found is used, otherwise an error will occur. Multiple 3D/4D arrays should not be stored in the same .mat file)


Available command line arguments are broken into four categories:

  1. Positional arguments: these are the input files. Input files are typically placed at the beginning of <COMMAND LINE ARGS>.
  2. Optional arguments: settings governing the analysis pipeline. See below for details.
  3. T2mapSEcorr/T2partSEcorr arguments: settings for computing the $T_2$-distribution and subsequent $T_2$-parts analysis. Required arguments are listed first; see below for the full parameter list, and see T2mapSEcorr and T2partSEcorr for parameter descriptions. Note: if no default is shown, the parameter is unused by default.
  4. B1 correction and stimulated echo correction: settings for controlling B1 correction and stimulated echo correction. These settings typically need not be modified. However, the following options are noteworthy: --SetFlipAngle allows for prescribing a fixed flip angle for all voxels instead of estimating the flip angle per-voxel; and --B1map allows for passing B1 maps (units of degrees) directly, replacing the flip angle estimation step.
  5. Additional save options: optional additional output maps
  6. BET arguments: settings for governing automatic brain mask generation using the BET brain extraction tool; see below for details.
usage: <PROGRAM> [-m MASK [MASK...]] [-o OUTPUT [OUTPUT...]] [--T2map]
                 [--T2part] [-q] [--dry] [--legacy]
                 [--MatrixSize MATRIXSIZE MATRIXSIZE MATRIXSIZE]
                 [--nTE NTE] [--TE TE] [--nT2 NT2]
                 [--T2Range T2RANGE T2RANGE] [--SPWin SPWIN SPWIN]
                 [--MPWin MPWIN MPWIN] [--Reg REG]
                 [--Chi2Factor CHI2FACTOR] [--T1 T1]
                 [--Sigmoid SIGMOID] [--Threshold THRESHOLD]
                 [--Progress] [--B1map B1MAP [B1MAP...]]
                 [--nRefAngles NREFANGLES]
                 [--nRefAnglesMin NREFANGLESMIN]
                 [--MinRefAngle MINREFANGLE]
                 [--SetFlipAngle SETFLIPANGLE]
                 [--RefConAngle REFCONANGLE] [--SaveDecayCurve]
                 [--SaveNNLSBasis] [--SaveRegParam]
                 [--SaveResidualNorm] [--bet] [--betargs BETARGS]
                 [--betpath BETPATH] [--compile] [input...]

positional arguments:
  input                 one or more input filenames. Valid file types
                        are limited to: .mat, .nii, .nii.gz, .par,
                        .xml, and .rec

optional arguments:
  -m, --mask MASK [MASK...]
                        one or more mask filenames. Masks are loaded
                        and subsequently applied to the corresponding
                        input files via elementwise multiplication.
                        The number of mask files must equal the number
                        of input files. Valid file types are the same
                        as for input files, and are limited to: .mat,
                        .nii, .nii.gz, .par, .xml, and .rec
  -o, --output OUTPUT [OUTPUT...]
                        one or more output directories. If not
                        specified, output file(s) will be stored in
                        the same location as the corresponding input
                        file(s). If one folder is passed, all output
                        files from all processed images will be stored
                        in the same folder. Otherwise, the number of
                        output folders must equal the number of input
                        files. Outputs are stored with the same
                        basename as the input files with additional
                        suffixes; see --T2map and --T2part
  --T2map               call T2mapSEcorr to compute T2 distributions
                        from 4D multi spin-echo input images. T2
                        distributions and T2 maps produced by
                        T2mapSEcorr are saved as MAT files with
                        extensions .t2dist.mat and .t2maps.mat
  --T2part              call T2partSEcorr to analyze 4D T2
                        distributions to produce parameter maps. If
                        --T2map is also passed, input 4D arrays are
                        interpreted as multi spin-echo images and T2
                        distributions are first computed by
                        T2mapSEcorr. If only --T2part is passed, input
                        4D arrays are interpreted as T2 distributions
                        and only T2partSEcorr is called. Output T2
                        parts are saved as a MAT file with extension
  -q, --quiet           suppress printing to the terminal. Note: all
                        terminal outputs, including errors and
                        warnings, are still printed to the log file
  --dry                 execute dry run of processing without saving
                        any results
  --legacy              use legacy settings and algorithms from the
                        original MATLAB pipeline. This ensures that
                        the same T2-distributions and T2-parts will be
                        produced as those from MATLAB. Note that
                        execution time will be much slower, and less
                        robust algorithms will be used

T2map/T2part required parameters:
                        matrix size of the magnitude image. Inferred
                        automatically as the first three dimensions of
                        the input 4D image (type: Int64)
  --nTE NTE             number of echoes of the magnitude image.
                        Inferred automatically as the last dimension
                        of the input 4D image (type: Int64)
  --TE TE               inter-echo spacing. Required when --T2map is
                        passed. (units: seconds) (type: Float64)
  --nT2 NT2             number of T2 components used in the
                        multi-exponential analysis. Required when
                        --T2map is passed. Inferred from fourth
                        dimension of input image if only --T2part and
                        not --T2map is passed (type: Int64)
                        minimum and maximum T2 values. T2 components
                        are logarithmically spaced between these
                        bounds. Required parameter. (units: seconds)
                        (type: Float64)
  --SPWin SPWIN SPWIN   minimum and maximum T2 values of the short
                        peak window. Required parameter when --T2part
                        is passed. (units: seconds) (type: Float64)
  --MPWin MPWIN MPWIN   minimum and maximum T2 values of the middle
                        peak window. Required parameter when --T2part
                        is passed. (units: seconds) (type: Float64)
  --Reg REG             routine used for choosing regularization
                        parameter. One of "lcurve", "gcv", "chi2", or
                        "none", representing L-curve based
                        regularization, generalized cross-validation
                        based regularization, --Chi2Factor based
                        Tikhonov regularization, and no
                        regularization, respectively. Required
  --Chi2Factor CHI2FACTOR
                        if --Reg="chi2", the T2 distribution is
                        regularized such that the chi^2 goodness of
                        fit is increased by a multiplicative factor
                        --Chi2Factor relative to the unregularized
                        solution. Required parameter when --Reg="chi2"
                        (type: Float64)

T2map/T2part optional parameters:
  --T1 T1               assumed value of longitudinal T1 relaxation.
                        (default: 1.0) (units: seconds) (type:
  --Sigmoid SIGMOID     replace the hard upper limit cutoff time of
                        the short peak window, SPWin[2], with a
                        smoothed sigmoidal cutoff function 'σ' scaled
                        and shifted such that σ(SPWin[2] +/- Sigmoid)
                        = 0.5 -/+ 0.4. Sigmoid is the time scale of
                        the smoothing. (units: seconds) (type:
  --Threshold THRESHOLD
                        first echo intensity cutoff for empty voxels.
                        Processing is skipped for voxels with
                        intensity <= --Threshold. (default: 0.0)
                        (units: signal magnitude) (type: Float64)
  --Progress            Print progress updates during T2 distribution
                        computation. Note: this flag is now
                        deprecated; progress updates are always
                        printed unless the --quiet flag is passed

B1 correction and stimulated echo correction:
  --B1map B1MAP [B1MAP...]
                        one or more B1 map filenames. The B1 maps must
                        have the same matrix sizes as the
                        corresponding images, and are assumed to
                        represent flip angles in units of degrees. The
                        number of B1 map files must equal the number
                        of input files. Valid file types are the same
                        as for input files, and are limited to: .mat,
                        .nii, .nii.gz, .par, .xml, and .rec. (units:
  --nRefAngles NREFANGLES
                        in estimating the local refocusing flip angle
                        to correct for B1 inhomogeneities, up to
                        --nRefAngles angles in the range
                        [--MinRefAngle, 180] are explicitly checked.
                        The optimal angle is then estimated by
                        interpolating between these observations.
                        (default: 32) (type: Int64)
                        initial number of angles in the range
                        [--MinRefAngle, 180] to check during flip
                        angle estimation before refinement near likely
                        optima. Setting --nRefAnglesMin equal to
                        --nRefAngles forces all candidate angles to be
                        checked before interpolation. (default: 5)
                        (type: Int64)
                        minimum refocusing angle for flip angle
                        estimation. (default: 50.0) (units: degrees)
                        (type: Float64)
                        to skip B1 inhomogeneity correction, use
                        --SetFlipAngle to assume a fixed refocusing
                        flip angle for all voxels. (units: degrees)
                        (type: Float64)
                        refocusing pulse control angle. The sequence
                        of flip angles used within the extended phase
                        graph algorithm to perform stimulated echo
                        correction is (90, 180, β, β, ..., β), where β
                        is the refocusing pulse control angle. For
                        typical multi spin-echo sequences this
                        parameter should not be changed. (default:
                        180.0) (units: degrees) (type: Float64)

Additional save options:
  --SaveDecayCurve      include a 4D array of the time domain decay
                        curves resulting from the NNLS fits in the
                        output maps dictionary
  --SaveNNLSBasis       include a 5D (or 2D if --SetFlipAngle is used)
                        array of NNLS basis matrices in the output
                        maps dictionary. Note: this 5D array is
                        extremely large for typical image sizes; in
                        most cases, this flag should only be set when
                        debugging small images
  --SaveRegParam        include 3D arrays of resulting regularization
                        parameters and χ² factors in the output maps
  --SaveResidualNorm    include a 3D array of the l2-norms of the
                        residuals from the NNLS fits in the output
                        maps dictionary

BET arguments:
  --bet                 use the BET brain extraction tool from the FSL
                        library of analysis tools to automatically
                        create a binary brain mask. Only voxels within
                        the binary mask will be analyzed. Note that if
                        a mask is passed explicitly with the --mask
                        flag, this mask will be used and the --bet
                        flag will be ignored
  --betargs BETARGS     BET command line interface arguments. Must be
                        passed as a single string with arguments
                        separated by commas or spaces, e.g. "-m -n".
                        The flag "-m" indicates that a binary mask
                        should be computed, and therefore will be
                        added to the list of arguments if not provided
                        (default: "-m -n -f 0.25 -R")
  --betpath BETPATH     path to BET executable (default: "bet")

Compiling DECAES (experimental):
  --compile             compile DECAES into a executable app and exit.
                        The DECAES app is stored in
                        `~/.julia/scratchspaces/<DECAES UUID>`, and a
                        symbolic link to the executable is created at
                        `~/.julia/bin/decaes`. The app can be run from
                        the command line using the syntax 'decaes
                        <DECAES arguments> --julia-args <Julia
                        arguments>'. Note: PackageCompiler.jl will be
                        automatically downloaded and installed upon
                        first use of the --compile flag

If desired, the $T_2$-distribution computation and the $T_2$-parts analysis may be performed separately:

  • When the --T2map flag is passed, or both --T2map and --T2part flags are passed, input image arrays should be 4D with data as (row, column, slice, echo)
  • When only the --T2part flag is passed, input image arrays should be 4D with data as (row, column, slice, $T_2$ bin)


DECAES will produce up to five output files, each with the input filename (without suffix) used as a prefix. For example, if the input file is called image.nii, the possible output files are:

  1. image.t2dist.mat: MATLAB file containing the 4D array of $T_2$-distributions (produced when --T2map flag is passed)
  2. image.t2maps.mat: MATLAB file containing $T_2$-distribution property maps and NNLS fit parameters; see T2mapSEcorr (produced when --T2map flag is passed)
  3. image.t2parts.mat: MATLAB file containing $T_2$-parts analysis results such as the MWF; see T2partSEcorr (produced when --T2part flag is passed)
  4. image.log: Log file containing the console output
  5. image.settings.txt: Copy of settings file which was named settings.txt (produced when passing settings as a file)

If the --dry flag is passed, none of the above files will be produced.


Multithreaded parallel processing can be enabled by passing the julia command line flag --threads=auto:

$ julia --threads=auto decaes.jl -- image.nii <COMMAND LINE ARGS>

This is highly recommended to speed up computation time, but is not strictly required.


Default options

Suppose you have a multi spin-echo image file image.nii which you would like to perform $T_2$ analysis on. We can call T2mapSEcorr and T2partSEcorr on the file image.nii using decaes.jl. We pass the required arguments with the appropriate flags and leave the remaining parameters at default values:

$ julia --threads=auto decaes.jl -- image.nii --T2map --T2part --TE 10e-3 --nT2 40 --T2Range 10e-3 2.0 --SPWin 10e-3 40e-3 --MPWin 40e-3 200.0e-3 --Reg lcurve

After a few seconds, the script should begin running with the following messages appearing as the script progresses (note that real images will take longer to process than this toy example):

[ Info: Starting DECAES v0.5.1 using Julia v1.9.3 with 1 threads
[ Info: Loading input file: image.nii.gz
[ Info: Done (0.22 seconds)
[ Info: Running T2mapSEcorr on file: image.nii.gz
┌ Info: T2-distribution analysis settings:
│ * Chi2Factor       : nothing
│ * legacy           : false
│ * MatrixSize       : (100, 100, 1)
│ * MinRefAngle      : 50.0
│ * nRefAngles       : 32
│ * nRefAnglesMin    : 5
│ * nT2              : 40
│ * nTE              : 32
│ * RefConAngle      : 180.0
│ * Reg              : lcurve
│ * SaveDecayCurve   : false
│ * SaveNNLSBasis    : false
│ * SaveRegParam     : false
│ * SaveResidualNorm : false
│ * SetFlipAngle     : nothing
│ * Silent           : false
│ * T1               : 1.0
│ * T2Range          : (0.01, 2.0)
│ * TE               : 0.01
│ * Threaded         : false
└ * Threshold        : 0.0
[ Info:   15%[=======>                                           ]  ETA: 0:01:02
[ Info:   22%[===========>                                       ]  ETA: 0:00:55
[ Info:   30%[===============>                                   ]  ETA: 0:00:49
[ Info:   38%[===================>                               ]  ETA: 0:00:44
[ Info:   46%[=======================>                           ]  ETA: 0:00:38
[ Info:   53%[===========================>                       ]  ETA: 0:00:33
[ Info:   61%[===============================>                   ]  ETA: 0:00:27
[ Info:   69%[==================================>                ]  ETA: 0:00:22
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[ Info:   84%[==========================================>        ]  ETA: 0:00:11
[ Info:   92%[==============================================>    ]  ETA: 0:00:06
[ Info:   99%[==================================================>]  ETA: 0:00:00
[ Info:  100%[===================================================] Time: 0:01:09
[ Info: Done (69.66 seconds)
[ Info: Saving T2 distribution to file: image.t2dist.mat
[ Info: Done (0.41 seconds)
[ Info: Saving T2 parameter maps to file: image.t2maps.mat
[ Info: Done (0.12 seconds)
[ Info: Running T2partSEcorr
┌ Info: T2-parts analysis settings:
│ * legacy     : false
│ * MatrixSize : (100, 100, 1)
│ * MPWin      : (0.04, 0.2)
│ * nT2        : 40
│ * Sigmoid    : nothing
│ * Silent     : false
│ * SPWin      : (0.01, 0.04)
│ * T2Range    : (0.01, 2.0)
└ * Threaded   : false
[ Info: Done (0.01 seconds)
[ Info: Saving T2 parts maps to file: image.t2parts.mat
[ Info: Done (0.0 seconds)
[ Info: Finished (70.75 seconds)

Settings files

As there are several required parameters, it is convenient to store settings for DECAES in a settings file. Using the same options from the previous section, we create a file settings.txt with the following contents:


If this file is located at /path/to/settings.txt, simply prefix the filepath with the @ character to have the file contents read into the main function:

$ julia --threads=auto decaes.jl -- @/path/to/settings.txt
  • The use of settings files is highly recommended for both reproducibility and for self-documentation. The input settings file will be automatically copied into the output folder for each processed image, with the image filename prepended. In this case, for example, the copied settings file would be called image.settings.txt
  • Only one flag or value is allowed per line within a settings file. Flags which require multiple inputs (e.g. --T2Range above) must use one line for each input
  • The extension of the settings file is ignored; .txt is arbitrary in this example
  • Though not strictly necessary, using full input- and output paths is recommended. This way, one doesn't rely on relative paths and can e.g. call julia /path/to/decaes.jl @/path/to/settings.txt from any directory

Default settings files

Suppose you have a default settings file default.txt, similar to the settings.txt file in the above section. Settings in default.txt can be individually overridden. For example, if we are interested in changing the number of $T_2$ bins nT2 to 60, but leaving all other parameters the same, run the following:

$ julia --threads=auto decaes.jl -- @/path/to/default.txt --nT2 60

Multiple input files

Multiple input files (possibly of different file types) can be passed in the obvious way:

$ julia --threads=auto decaes.jl -- image1.nii image2.mat image3.nii.gz image4.par <COMMAND LINE ARGS>

Equivalently, place multiple image paths at the top of your settings file, with each path on a new line.

Specify output folder

By default, output files are saved in the same location as the corresponding input file. If you'd like to save them in a different folder, you can use the -o or --output flag:

$ julia --threads=auto decaes.jl -- image.nii --output /path/to/output/folder/ <COMMAND LINE ARGS>

The requested output folder will be created if it does not already exist.

Equivalently, add --output and /path/to/output/folder/ as consecutive lines in your settings file.

Passing image masks

Image masks can be passed into DECAES using the -m or --mask flag:

$ julia --threads=auto decaes.jl -- image.nii --mask /path/to/mask.nii <COMMAND LINE ARGS>

The mask file is loaded and applied to the input image via elementwise multiplication over the spatial dimensions, e.g. the mask is applied to each echo of a 4D multi-echo input image.

If multiple image files are passed, multiple corresponding mask files can be passed, too:

$ julia --threads=auto decaes.jl -- image1.nii image2.mat --mask /path/to/mask1.mat /path/to/mask2.nii.gz <COMMAND LINE ARGS>

Equivalently, add --mask, /path/to/mask1.mat, /path/to/mask2.mat, ... as consecutive lines in your settings file.


If input images have been manually masked such that they are zero outside regions of interest, a mask need not be passed. The --Threshold parameter of T2mapSEcorr controls a first echo intensity cutoff threshold (default value 0.0), below which voxels are automatically skipped during processing

Automatic brain masking with BET

The BET brain extraction tool from the FSL library of analysis tools can be used to automatically generate a brain mask prior to analysis. Only voxels within the generated brain mask will be processed, greatly reducing analysis time. To use BET, pass the --bet flag:

$ julia --threads=auto decaes.jl -- image.nii --bet <COMMAND LINE ARGS>

If bet is not on your system path, you can pass the path to the bet binary with the --betpath flag. Additionally, you can pass arguments to bet with the --betargs flag:

$ julia --threads=auto decaes.jl -- image.nii --bet --betpath /path/to/bet --betargs '-m -n' <COMMAND LINE ARGS>

Note that bet arguments must be passed as a single string to --betargs, separated by spaces, as shown above.

Equivalently, add --bet, --betpath, /path/to/bet, --betargs, -m -n ... as consecutive lines in your settings file.


If a mask file is passed using the --mask flag, the --bet flag will be ignored and the mask file will be used

Legacy options

During the port from MATLAB to Julia, some algorithms were improved using computationally more efficient algorithms, and some default parameters were modified or removed as well. This may cause small differences in output parameter maps. As an example, the flip angle optimization procedure requires finding the root of a cubic spline. In MATLAB this was performed by evaluating the spline on a very fine mesh and choosing the value nearest zero. During profiling it was found that this was a time consuming operation, and therefore in Julia this was replaced by an efficient rootfinding method tailored for cubic splines.

The differences due to algorithmic changes like the one above are quite small. For example, most tests in the DECAES test suite will pass when using a relative tolerance of $10^{-3}$, and almost all tests pass with a relative tolerance of $10^{-2}$. That is to say that nearly all outputs are identical to 3 or more significant digits, which includes $T_2$-distributions, MWF maps, etc. It should be emphasized, though, that as these differences arise from improved algorithms, any discrepencies are merely small improvements.

The --legacy flag is available if exact reproducibility is required compared to the MATLAB version. This will ensure that all outputs match to nearly machine precision (a relative tolerance of $10^{-10}$ is used during testing). Note however that the --legacy flag may cause a significant slowdown in processing time due to less efficient algorithms being used internally, and is therefore not recommended unless absolutely necessary. Differences due to changes in default parameters can always be overridden by passing in the desired value explicitly without the need for the --legacy flag.