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
:
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:
- NIfTI file with extension
.nii
, or gzip compressed NIfTI file with extension.nii.gz
. See NIfTI.jl for more information. - MATLAB file with extension
.mat
. Note:.mat
files saved in the oldest formatv4
are not supported, but all newer formats (v6
,v7
, andv7.3
) are supported. See MAT.jl for more information. - Philips PAR/REC file pair with extensions
.par
and.rec
(or.PAR
and.REC
). - 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)
Arguments
Available command line arguments are broken into four categories:
- Positional arguments: these are the input files. Input files are typically placed at the beginning of
<COMMAND LINE ARGS>
. - Optional arguments: settings governing the analysis pipeline. See below for details.
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 seeT2mapSEcorr
andT2partSEcorr
for parameter descriptions. Note: if no default is shown, the parameter is unused by default.- 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] [--T2map] [--T2part]
[-q] [--dry] [--legacy]
[--MatrixSize MATRIXSIZE MATRIXSIZE MATRIXSIZE]
[--nTE NTE] [--nT2 NT2] [--TE TE]
[--T2Range T2RANGE T2RANGE] [--SPWin SPWIN SPWIN]
[--MPWin MPWIN MPWIN] [--Chi2Factor CHI2FACTOR]
[--MinRefAngle MINREFANGLE] [--nRefAngles NREFANGLES]
[--nRefAnglesMin NREFANGLESMIN]
[--RefConAngle REFCONANGLE] [--Reg REG]
[--SaveDecayCurve] [--SaveNNLSBasis] [--SaveRegParam]
[--SaveResidualNorm] [--SetFlipAngle SETFLIPANGLE]
[--Sigmoid SIGMOID] [--Silent] [--T1 T1]
[--Threshold THRESHOLD] [--bet] [--betargs BETARGS]
[--betpath BETPATH] 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 directory. If not specified, output
file(s) will be stored in the same location as
the corresponding input file(s). Outputs are
stored with the same basename as inputs and
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
.t2parts.mat
-q, --quiet suppress printing to the terminal. Note: all
terminal output, including errors and
warnings, is 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 version. This ensures that the
exact same T2-distributions and T2-parts will
be produced as those from MATLAB (to machine
precision). Note that execution time will be
much slower.
T2mapSEcorr/T2partSEcorr arguments:
--MatrixSize MATRIXSIZE MATRIXSIZE MATRIXSIZE
Required parameter; inferred from first three
dimensions of input image
--nTE NTE Required parameter; inferred from fourth
dimension of input image if --T2map is passed
--nT2 NT2 Required parameter; inferred from fourth
dimension of input image if --T2part (and not
--T2map) is passed
--TE TE Required parameter when --T2map is passed
--T2Range T2RANGE T2RANGE
Required parameter when --T2map or --T2part is
passed
--SPWin SPWIN SPWIN Required parameter when --T2part is passed
--MPWin MPWIN MPWIN Required parameter when --T2part is passed
--Chi2Factor CHI2FACTOR
(default: 1.02)
--MinRefAngle MINREFANGLE
(default: 50.0)
--nRefAngles NREFANGLES
(default: 32)
--nRefAnglesMin NREFANGLESMIN
(default: 5)
--RefConAngle REFCONANGLE
(default: 180.0)
--Reg REG (default: "chi2")
--SaveDecayCurve
--SaveNNLSBasis
--SaveRegParam
--SaveResidualNorm
--SetFlipAngle SETFLIPANGLE
--Sigmoid SIGMOID
--Silent
--T1 T1 (default: 1.0)
--Threshold THRESHOLD
(default: 0.0)
BET arguments:
--bet use the BET brain extraction tool from the FSL
library of analyis 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 --bet will be
ignored.
--betargs BETARGS BET optional arguments. Must be passed as a
single string with arguments separated by
spaces, e.g. '-m -n'. The flag '-m' creates
the binary mask and 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")
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)
Outputs
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:
image.t2dist.mat
: MATLAB file containing the 4D array of $T_2$-distributions (produced when--T2map
flag is passed)image.t2maps.mat
: MATLAB file containing $T_2$-distribution property maps and NNLS fit parameters; seeT2mapSEcorr
(produced when--T2map
flag is passed)image.t2parts.mat
: MATLAB file containing $T_2$-parts analysis results such as the MWF; seeT2partSEcorr
(produced when--T2part
flag is passed)image.log
: Log file containing the console outputimage.settings.txt
: Copy of settings file which was namedsettings.txt
(produced when passing settings as a file)
If the --dry
flag is passed, none of the above files will be produced.
Multithreading
Multithreaded parallel processing can be enabled by setting the JULIA_NUM_THREADS
environment variable as follows:
$ export JULIA_NUM_THREADS=1 # set JULIA_NUM_THREADS > 1 to enable parallel processing
$ julia decaes.jl image.nii <COMMAND LINE ARGS>
This is highly recommended to speed up computation time, but is not strictly required.
From the Julia documentation:
[The keyword
export
] works on bourne shells on Linux and OSX. Note that if you're using a C shell on these platforms, you should use the keywordset
instead ofexport
. If you're on Windows, start up the command line in the location ofjulia.exe
and useset
instead ofexport
.
Examples
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:
$ export JULIA_NUM_THREADS=1
$ julia 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
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 with 1 threads
[ Info: Loading input file: image.nii.gz ...
[ Info: Done (0.16 seconds)
[ Info: Running T2mapSEcorr on file: image.nii.gz ...
┌ Info: T2-Distribution analysis settings:
│ Chi2Factor : 1.02
│ legacy : false
│ MatrixSize : (100, 100, 1)
│ MinRefAngle : 50.0
│ nRefAngles : 32
│ nRefAnglesMin : 5
│ nT2 : 40
│ nTE : 32
│ RefConAngle : 180.0
│ Reg : chi2
│ SaveDecayCurve : false
│ SaveNNLSBasis : false
│ SaveRegParam : false
│ SaveResidualNorm : false
│ SetFlipAngle : nothing
│ Silent : false
│ T1 : 1.0
│ T2Range : (0.01, 2.0)
│ TE : 0.01
└ Threshold : 0.0
[ Info: [ 0%] -- Elapsed Time: 00h:00m:00s -- Estimated Time Remaining: --h:--m:--s
[ Info: [ 26%] -- Elapsed Time: 00h:00m:15s -- Estimated Time Remaining: 00h:00m:42s
[ Info: [ 52%] -- Elapsed Time: 00h:00m:30s -- Estimated Time Remaining: 00h:00m:27s
[ Info: [ 78%] -- Elapsed Time: 00h:00m:45s -- Estimated Time Remaining: 00h:00m:12s
[ Info: [100%] -- Elapsed Time: 00h:00m:57s -- Estimated Time Remaining: 00h:00m:00s
[ Info: Done (57.28 seconds)
[ Info: Saving T2 distribution to file: image.t2dist.mat ...
[ Info: Done (0.36 seconds)
[ Info: Saving T2 parameter maps to file: image.t2maps.mat ...
[ Info: Done (0.13 seconds)
[ Info: Running T2partSEcorr ...
┌ Info: T2-part 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)
[ Info: Done (0.12 seconds)
[ Info: Saving T2 parts maps to file: image.t2parts.mat ...
[ Info: Done (0.0 seconds)
[ Info: Finished (58.08 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:
/path/to/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
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:
$ export JULIA_NUM_THREADS=1
$ julia 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:
$ export JULIA_NUM_THREADS=1
$ julia 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:
$ export JULIA_NUM_THREADS=1
$ julia 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:
$ export JULIA_NUM_THREADS=1
$ julia 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:
$ export JULIA_NUM_THREADS=1
$ julia 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, a mask can be passed for each input image (note that each mask file can be any valid file type):
$ export JULIA_NUM_THREADS=1
$ julia 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:
$ export JULIA_NUM_THREADS=1
$ julia 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:
$ export JULIA_NUM_THREADS=1
$ julia 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 (e.g. --SPWin 0.014 0.040
) without the need for the --legacy
flag.
Default options with the --legacy
flag
usage: <PROGRAM> [-m MASK [MASK...]] [-o OUTPUT] [--T2map] [--T2part]
[-q] [--dry] [--legacy]
[--MatrixSize MATRIXSIZE MATRIXSIZE MATRIXSIZE]
[--nTE NTE] [--nT2 NT2] [--TE TE]
[--T2Range T2RANGE T2RANGE] [--SPWin SPWIN SPWIN]
[--MPWin MPWIN MPWIN] [--Chi2Factor CHI2FACTOR]
[--MinRefAngle MINREFANGLE] [--nRefAngles NREFANGLES]
[--nRefAnglesMin NREFANGLESMIN]
[--RefConAngle REFCONANGLE] [--Reg REG]
[--SaveDecayCurve] [--SaveNNLSBasis] [--SaveRegParam]
[--SaveResidualNorm] [--SetFlipAngle SETFLIPANGLE]
[--Sigmoid SIGMOID] [--Silent] [--T1 T1]
[--Threshold THRESHOLD] [--bet] [--betargs BETARGS]
[--betpath BETPATH] 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 directory. If not specified, output
file(s) will be stored in the same location as
the corresponding input file(s). Outputs are
stored with the same basename as inputs and
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
.t2parts.mat
-q, --quiet suppress printing to the terminal. Note: all
terminal output, including errors and
warnings, is 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 version. This ensures that the
exact same T2-distributions and T2-parts will
be produced as those from MATLAB (to machine
precision). Note that execution time will be
much slower.
T2mapSEcorr/T2partSEcorr arguments:
--MatrixSize MATRIXSIZE MATRIXSIZE MATRIXSIZE
Required parameter; inferred from first three
dimensions of input image
--nTE NTE Required parameter; inferred from fourth
dimension of input image if --T2map is passed
--nT2 NT2 Required parameter; inferred from fourth
dimension of input image if --T2part (and not
--T2map) is passed
--TE TE Required parameter when --T2map is passed
--T2Range T2RANGE T2RANGE
Required parameter when --T2map or --T2part is
passed
--SPWin SPWIN SPWIN Required parameter when --T2part is passed
--MPWin MPWIN MPWIN Required parameter when --T2part is passed
--Chi2Factor CHI2FACTOR
(default: 1.02)
--MinRefAngle MINREFANGLE
(default: 50.0)
--nRefAngles NREFANGLES
(default: 8)
--nRefAnglesMin NREFANGLESMIN
(default: 8)
--RefConAngle REFCONANGLE
(default: 180.0)
--Reg REG (default: "chi2")
--SaveDecayCurve
--SaveNNLSBasis
--SaveRegParam
--SaveResidualNorm
--SetFlipAngle SETFLIPANGLE
--Sigmoid SIGMOID
--Silent
--T1 T1 (default: 1.0)
--Threshold THRESHOLD
(default: 200.0)
BET arguments:
--bet use the BET brain extraction tool from the FSL
library of analyis 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 --bet will be
ignored.
--betargs BETARGS BET optional arguments. Must be passed as a
single string with arguments separated by
spaces, e.g. '-m -n'. The flag '-m' creates
the binary mask and 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")