[med-svn] [Git][med-team/bart][master-contrib] update commands.txt added in Debian patch
Martin Uecker (@uecker-guest)
gitlab at salsa.debian.org
Sun Sep 25 14:35:45 BST 2022
Martin Uecker pushed to branch master-contrib at Debian Med / bart
Commits:
33c1e776 by Martin Uecker at 2022-09-25T15:25:39+02:00
update commands.txt added in Debian patch
- - - - -
1 changed file:
- debian/patches/0005-do-not-update-doc-commands.txt-automatically.patch
Changes:
=====================================
debian/patches/0005-do-not-update-doc-commands.txt-automatically.patch
=====================================
@@ -4,8 +4,8 @@ Subject: do not update doc/commands.txt automatically
---
Makefile | 4 +-
- doc/commands.txt | 1403 ++++++++++++++++++++++++++++++++++++++++++++++++++++++
- 2 files changed, 1405 insertions(+), 2 deletions(-)
+ doc/commands.txt | 1593 ++++++++++++++++++++++++++++++++++++++++++++++++++++++
+ 2 files changed, 1595 insertions(+), 2 deletions(-)
create mode 100644 doc/commands.txt
diff --git a/Makefile b/Makefile
@@ -32,1218 +32,1407 @@ index 46a8891..15dd73b 100644
touch isclean
diff --git a/doc/commands.txt b/doc/commands.txt
new file mode 100644
-index 0000000..2650973
+index 0000000..10676f7
--- /dev/null
+++ b/doc/commands.txt
-@@ -0,0 +1,1403 @@
+@@ -0,0 +1,1593 @@
+AUTOGENERATED. DO NOT EDIT.
+
+
+--avg--
+
-+Usage: avg [-w] <bitmask> <input> <output>
++Usage: avg [-w] bitmask <input> <output>
+
+Calculates (weighted) average along dimensions specified by bitmask.
+
-+-w weighted average
-+-h help
++-w weighted average
++-h help
+
+
+--bench--
+
-+Usage: bench [-T] [-S] [-s d] [<output>]
++Usage: bench [-T] [-S] [-s d] [<output>]
+
+Performs a series of micro-benchmarks.
+
-+-T varying number of threads
-+-S varying problem size
-+-s flags select benchmarks
-+-h help
++-T varying number of threads
++-S varying problem size
++-s flags select benchmarks
++-h help
+
+
+--bin--
+
-+Usage: bin [-l d] [-o] [-R d] [-C d] [-r ...] [-c ...] [-a d] [-A d] [-x <string>] <label> <src> <dst>
++Usage: bin [-l d] [-o] [-R d] [-C d] [-a d] [-O f:f] [-M] <label> <src> <dst>
+
+Binning
+
-+
-+-l dim Bin according to labels: Specify cluster dimension
-+-o Reorder according to labels
-+-R n_resp Quadrature Binning: Number of respiratory labels
-+-C n_card Quadrature Binning: Number of cardiac labels
-+-r x:y (Respiration: Eigenvector index)
-+-c x:y (Cardiac motion: Eigenvector index)
-+-a window Quadrature Binning: Moving average
-+-A window (Quadrature Binning: Cardiac moving average window)
-+-x file (Output filtered cardiac EOFs)
-+-h help
++-l dim Bin according to labels: Specify cluster dimension
++-o Reorder according to labels
++-R n_resp Quadrature Binning: Number of respiratory labels
++-C n_card Quadrature Binning: Number of cardiac labels
++-a window Quadrature Binning: Moving average
++-O [r:c]deg Quadrature Binning: Angle offset for resp and card.
++-M Amplitude binning
++-h help
+
+
+--bitmask--
+
-+Usage: bitmask [-b] -b <bitmask> | <dim1> ... <dimN>
++Usage: bitmask [-b] [dim1 ... dimN ]
+
+Convert between a bitmask and set of dimensions.
+
-+-b dimensions from bitmask
-+-h help
++-b dimensions from bitmask, use with exactly one argument
++-h help
+
+
+--cabs--
+
-+Usage: cabs <input> <output>
++Usage: cabs <input> <output>
+
+Absolute value of array (|<input>|).
+
-+-h help
++-h help
+
+
+--caldir--
+
-+Usage: caldir cal_size <input> <output>
++Usage: caldir cal_size <input> <output>
+
+Estimates coil sensitivities from the k-space center using
+a direct method (McKenzie et al.). The size of the fully-sampled
+calibration region is automatically determined but limited by
+{cal_size} (e.g. in the readout direction).
+
-+-h help
++-h help
+
+
+--calmat--
+
-+Usage: calmat [-k ...] [-r ...] <kspace> <calibration matrix>
++Usage: calmat [-k d:d:d] [-r d:d:d] <kspace> <calibration_matrix>
+
+Compute calibration matrix.
+
-+-k ksize kernel size
-+-r cal_size Limits the size of the calibration region.
-+-h help
++-k ksize kernel size
++-r cal_size Limits the size of the calibration region.
++-h help
+
+
+--carg--
+
-+Usage: carg <input> <output>
++Usage: carg <input> <output>
+
+Argument (phase angle).
+
-+-h help
++-h help
+
+
+--casorati--
+
-+Usage: casorati dim1 kern1 dim2 kern2 ... dimn kernn <input> <output>
-+
-+Casorati matrix with kernel (kern1, ..., kernn) along dimensions (dim1, ..., dimn).
++Usage: casorati dim1 kern1 ... dimN kernN <input> <output>
+
++Casorati matrix with kernel (kern1, ..., kernN) along dimensions (dim1, ..., dimN).
+
-+-h help
++-h help
+
+
+--cc--
+
-+Usage: cc [-p d] [-M] [-r ...] [-A] [-S ...] [-G ...] [-E ...] <kspace> <coeff>|<proj_kspace>
++Usage: cc [-p d] [-M] [-r d:d:d] [-A] [-S] [-G] [-E] <kspace> <coeff|proj_kspace>
+
+Performs coil compression.
+
-+-p N perform compression to N virtual channels
-+-M output compression matrix
-+-r S size of calibration region
-+-A use all data to compute coefficients
-+-S type: SVD
-+-G type: Geometric
-+-E type: ESPIRiT
-+-h help
++-p N perform compression to N virtual channels
++-M output compression matrix
++-r S size of calibration region
++-A use all data to compute coefficients
++-S type: SVD
++-G type: Geometric
++-E type: ESPIRiT
++-h help
+
+
+--ccapply--
+
-+Usage: ccapply [-p d] [-u] [-t] [-S ...] [-G ...] [-E ...] <kspace> <cc_matrix> <proj_kspace>
++Usage: ccapply [-p d] [-u] [-t] [-S] [-G] [-E] <kspace> <cc_matrix> <proj_kspace>
+
+Apply coil compression forward/inverse operation.
+
-+-p N perform compression to N virtual channels
-+-u apply inverse operation
-+-t don't apply FFT in readout
-+-S type: SVD
-+-G type: Geometric
-+-E type: ESPIRiT
-+-h help
++-p N perform compression to N virtual channels
++-u apply inverse operation
++-t don't apply FFT in readout
++-S type: SVD
++-G type: Geometric
++-E type: ESPIRiT
++-h help
+
+
+--cdf97--
+
-+Usage: cdf97 [-i] bitmask <input> <output>
++Usage: cdf97 [-i] bitmask <input> <output>
+
+Perform a wavelet (cdf97) transform.
+
-+
-+-i inverse
-+-h help
++-i inverse
++-h help
+
+
+--circshift--
+
-+Usage: circshift dim shift <input> <output>
++Usage: circshift dim shift <input> <output>
+
+Perform circular shift along {dim} by {shift} elements.
+
-+-h help
++-h help
+
+
+--conj--
+
-+Usage: conj <input> <output>
++Usage: conj <input> <output>
+
+Compute complex conjugate.
+
-+-h help
++-h help
+
+
+--conv--
+
-+Usage: conv bitmask <input> <kernel> <output>
++Usage: conv bitmask <input> <kernel> <output>
+
+Performs a convolution along selected dimensions.
+
-+-h help
++-h help
+
+
+--conway--
+
-+Usage: conway [-P] [-n d] <input> <output>
++Usage: conway [-P] [-n d] <input> <output>
+
+Conway's game of life.
+
-+
-+-P periodic boundary conditions
-+-n # nr. of iterations
-+-h help
++-P periodic boundary conditions
++-n # nr. of iterations
++-h help
+
+
+--copy--
+
-+Usage: copy [dim1 pos1 ... dimn posn] <input> <output>
++Usage: copy [dim1 pos1 ... dimN posN ] <input> <output>
+
+Copy an array (to a given position in the output file - which then must exist).
+
-+-h help
++-h help
+
+
+--cpyphs--
+
-+Usage: cpyphs <input> <output
++Usage: cpyphs <input> <output>
+
+Copy phase from <input> to <output>.
+
-+-h help
++-h help
+
+
+--creal--
+
-+Usage: creal <input> <output>
++Usage: creal <input> <output>
+
+Real value.
+
-+-h help
++-h help
+
+
+--crop--
+
-+Usage: crop dimension size <input> <output>
++Usage: crop dimension size <input> <output>
+
+Extracts a sub-array corresponding to the central part of {size} along {dimension}
+
-+-h help
++-h help
+
+
+--delta--
+
-+Usage: delta dims flags size out
++Usage: delta dims flags size <out>
+
+Kronecker delta.
+
-+-h help
++-h help
+
+
+--ecalib--
+
-+Usage: ecalib [-t f] [-c f] [-k ...] [-r ...] [-m d] [-S] [-W] [-I] [-1] [-P] [-v f] [-a] [-d d] <kspace> <sensitivites> [<ev-maps>]
++Usage: ecalib [-t f] [-c f] [-k d:d:d] [-r d:d:d] [-m d] [-S] [-W] [-I] [-1] [-P] [-v f] [-a] [-d d] <kspace> <sensitivities> [<ev-maps>]
+
+Estimate coil sensitivities using ESPIRiT calibration.
+Optionally outputs the eigenvalue maps.
+
-+-t threshold This determined the size of the null-space.
-+-c crop_value Crop the sensitivities if the eigenvalue is smaller than {crop_value}.
-+-k ksize kernel size
-+-r cal_size Limits the size of the calibration region.
-+-m maps Number of maps to compute.
-+-S create maps with smooth transitions (Soft-SENSE).
-+-W soft-weighting of the singular vectors.
-+-I intensity correction
-+-1 perform only first part of the calibration
-+-P Do not rotate the phase with respect to the first principal component
-+-v variance Variance of noise in data.
-+-a Automatically pick thresholds.
-+-d level Debug level
-+-h help
++-t threshold This determined the size of the null-space.
++-c crop_value Crop the sensitivities if the eigenvalue is smaller than {crop_value}.
++-k ksize kernel size
++-r cal_size Limits the size of the calibration region.
++-m maps Number of maps to compute.
++-S create maps with smooth transitions (Soft-SENSE).
++-W soft-weighting of the singular vectors.
++-I intensity correction
++-1 perform only first part of the calibration
++-P Do not rotate the phase with respect to the first principal component
++-v variance Variance of noise in data.
++-a Automatically pick thresholds.
++-d level Debug level
++-h help
+
+
+--ecaltwo--
+
-+Usage: ecaltwo [-c f] [-m d] [-S] x y z <input> <sensitivities> [<ev_maps>]
++Usage: ecaltwo [-c f] [-m d] [-S] x y z <input> <sensitivities> [<ev-maps>]
+
+Second part of ESPIRiT calibration.
+Optionally outputs the eigenvalue maps.
+
-+-c crop_value Crop the sensitivities if the eigenvalue is smaller than {crop_value}.
-+-m maps Number of maps to compute.
-+-S Create maps with smooth transitions (Soft-SENSE).
-+-h help
++-c crop_value Crop the sensitivities if the eigenvalue is smaller than {crop_value}.
++-m maps Number of maps to compute.
++-S Create maps with smooth transitions (Soft-SENSE).
++-h help
++
++
++--epg--
++
++Usage: epg [-C] [-M] [-H] [-F] [-S] [-B] [-1 f] [-2 f] [-b f] [-o f] [-r f] [-e f] [-f f] [-s d] [-n d] [-u d] [-v d] <signal intensity> [<configuration states>] [<(rel.) signal derivatives>] [<configuration derivatives>]
++
++Simulate MR pulse sequence based on Extended Phase Graphs (EPG)
++
++-C CPMG
++-M fmSSFP
++-H Hyperecho
++-F FLASH
++-S Spinecho
++-B bSSFP
++-1 T1 T1 [units of time]
++-2 T2 T2 [units of time]
++-b B1 relative B1 [unitless]
++-o OFF off-resonance [units of inverse time]
++-r TR repetition time [units of time]
++-e TE echo time [units of time]
++-f FA flip angle [degrees]
++-s SP spoiling (0: ideal, 1: conventional RF, 2: random RF)
++-n N number of pulses
++-u U unknowns as bitmask (0: T1, 1: T2, 2: B1, 3: off-res)
++-v V verbosity level
++-h help
+
+
+--estdelay--
+
-+Usage: estdelay [-R] [-p d] [-n d] [-r f] <trajectory> <data> [<qf>]
++Usage: estdelay [-R] [-p d] [-n d] [-r f] <trajectory> <data> [<qf>]
+
+Estimate gradient delays from radial data.
+
-+-R RING method
-+-p p [RING] Padding
-+-n n [RING] Number of intersecting spokes
-+-r r [RING] Central region size
-+-h help
++-R RING method
++-p p [RING] Padding
++-n n [RING] Number of intersecting spokes
++-r r [RING] Central region size
++-h help
+
+
+--estdims--
+
-+Usage: estdims <traj>
++Usage: estdims <traj>
+
+Estimate image dimension from non-Cartesian trajectory.
+Assume trajectory scaled to -DIM/2 to DIM/2 (ie dk=1/FOV=1)
+
-+-h help
++-h help
+
+
+--estshift--
+
-+Usage: estshift flags <arg1> <arg2>
++Usage: estshift flags <arg1> <arg2>
+
+Estimate sub-pixel shift.
+
-+-h help
++-h help
+
+
+--estvar--
+
-+Usage: estvar [-k ...] [-r ...] <kspace>
++Usage: estvar [-k d:d:d] [-r d:d:d] <kspace>
+
+Estimate the noise variance assuming white Gaussian noise.
+
-+-k ksize kernel size
-+-r cal_size Limits the size of the calibration region.
-+-h help
++-k ksize kernel size
++-r cal_size Limits the size of the calibration region.
++-h help
+
+
+--extract--
+
-+Usage: extract dim1 start1 end1 ... dimn startn endn <input> <output>
++Usage: extract dim1 start1 end1 ... dimN startN endN <input> <output>
+
+Extracts a sub-array along dims from index start to (not including) end..
+
-+
-+-h help
++-h help
+
+
+--fakeksp--
+
-+Usage: fakeksp [-r] <image> <kspace> <sens> <output>
++Usage: fakeksp [-r] <image> <kspace> <sens> <output>
+
+Recreate k-space from image and sensitivities.
+
-+-r replace measured samples with original values
-+-h help
++-r replace measured samples with original values
++-h help
+
+
+--fft--
+
-+Usage: fft [-u] [-i] [-n] bitmask <input> <output>
++Usage: fft [-u] [-i] [-n] bitmask <input> <output>
+
+Performs a fast Fourier transform (FFT) along selected dimensions.
+
-+-u unitary
-+-i inverse
-+-n un-centered
-+-h help
++-u unitary
++-i inverse
++-n un-centered
++-h help
+
+
+--fftmod--
+
-+Usage: fftmod [-i] bitmask <input> <output>
++Usage: fftmod [-i] bitmask <input> <output>
+
+Apply 1 -1 modulation along dimensions selected by the {bitmask}.
+
-+
-+-i inverse
-+-h help
++-i inverse
++-h help
+
+
+--fftrot--
+
-+Usage: fftrot dim1 dim2 theta <input> <output>
++Usage: fftrot dim1 dim2 theta <input> <output>
+
+Performs a rotation using Fourier transform (FFT) along selected dimensions.
+
-+-h help
++-h help
+
+
+--fftshift--
+
-+Usage: fftshift bitmask <input> <output>
++Usage: fftshift [-b] bitmask <input> <output>
+
+Apply fftshift along dimensions selected by the {bitmask}.
+
-+-h help
++-b apply ifftshift
++-h help
+
+
+--filter--
+
-+Usage: filter [-m d] [-l d] <input> <output>
++Usage: filter [-m d] [-l d] [-G] [-a d] <input> <output>
+
+Apply filter.
+
-+
-+-m dim median filter along dimension dim
-+-l len length of filter
-+-h help
++-m dim median filter along dimension dim
++-l len length of filter
++-G geometric median
++-a dim Moving average filter along dimension dim
++-h help
+
+
+--flatten--
+
-+Usage: flatten <input> <output>
++Usage: flatten <input> <output>
+
+Flatten array to one dimension.
+
-+-h help
++-h help
+
+
+--flip--
+
-+Usage: flip bitmask <input> <output>
++Usage: flip bitmask <input> <output>
+
+Flip (reverse) dimensions specified by the {bitmask}.
+
-+-h help
++-h help
+
+
+--fmac--
+
-+Usage: fmac [-A] [-C] [-s d] <input1> [<input2>] <output>
++Usage: fmac [-A] [-C] [-s d] <input1> [<input2>] <output>
+
+Multiply <input1> and <input2> and accumulate in <output>.
+If <input2> is not specified, assume all-ones.
+
-+-A add to existing output (instead of overwriting)
-+-C conjugate input2
-+-s b squash dimensions selected by bitmask b
-+-h help
++-A add to existing output (instead of overwriting)
++-C conjugate input2
++-s b squash dimensions selected by bitmask b
++-h help
++
++
++--fovshift--
++
++Usage: fovshift [-t <file>] [-s f:f:f] <input> <output>
++
++Shifts FOV.
++
++-t file k-space trajectory
++-s X:Y:Z FOV shift
++-h help
+
+
+--homodyne--
+
-+Usage: homodyne [-r f] [-I] [-C] [-P <string>] [-n] dim fraction <input> <output>
++Usage: homodyne [-r f] [-I] [-C] [-P <file>] [-n] dim fraction <input> <output>
+
+Perform homodyne reconstruction along dimension dim.
+
-+-r alpha Offset of ramp filter, between 0 and 1. alpha=0 is a full ramp, alpha=1 is a horizontal line
-+-I Input is in image domain
-+-C Clear unacquired portion of kspace
-+-P phase_ref> Use <phase_ref> as phase reference
-+-n use uncentered ffts
-+-h help
++-r alpha Offset of ramp filter, between 0 and 1. alpha=0 is a full ramp, alpha=1 is a horizontal line
++-I Input is in image domain
++-C Clear unacquired portion of kspace
++-P phase_ref> Use <phase_ref> as phase reference
++-n use uncentered ffts
++-h help
++
++
++--ictv--
++
++Usage: ictv [-i d] [-u f] lambda flags flags <input> <output>
++
++Infimal convolution of total variation along dims specified by flags.
++
++-i i max. iterations
++-u rho rho in ADMM
++-h help
+
+
+--index--
+
-+Usage: index dim size name
++Usage: index dim size <name>
+
+Create an array counting from 0 to {size-1} in dimensions {dim}.
+
-+-h help
++-h help
+
+
+--invert--
+
-+Usage: invert <input> <output>
++Usage: invert <input> <output>
+
+Invert array (1 / <input>). The output is set to zero in case of divide by zero.
+
-+-h help
++-h help
+
+
+--itsense--
+
-+Usage: itsense alpha <sensitivities> <kspace> <pattern> <image>
++Usage: itsense alpha <sensitivities> <kspace> <pattern> <output>
+
+A simplified implementation of iterative sense reconstruction
+with l2-regularization.
+
-+-h help
++-h help
+
+
+--join--
+
-+Usage: join [-a] dimension <input1> ... <inputn> <output>
++Usage: join [-a] dimension <input>1> ... <input>N> <output>
+
+Join input files along {dimensions}. All other dimensions must have the same size.
+ Example 1: join 0 slice_001 slice_002 slice_003 full_data
+ Example 2: join 0 `seq -f "slice_%%03g" 0 255` full_data
+
-+
-+-a append - only works for cfl files!
-+-h help
++-a append - only works for cfl files!
++-h help
+
+
+--looklocker--
+
-+Usage: looklocker [-t f] [-D f] <input> <output>
++Usage: looklocker [-t f] [-D f] <input> <output>
+
+Compute T1 map from M_0, M_ss, and R_1*.
+
-+
-+-t threshold Pixels with M0 values smaller than {threshold} are set to zero.
-+-D delay Time between the middle of inversion pulse and the first excitation.
-+-h help
++-t threshold Pixels with M0 values smaller than {threshold} are set to zero.
++-D delay Time between the middle of inversion pulse and the first excitation.
++-h help
+
+
+--lrmatrix--
+
-+Usage: lrmatrix [-d] [-i d] [-m d] [-f d] [-j d] [-k d] [-N] [-s] [-l d] [-o <string>] <input> <output>
++Usage: lrmatrix [-d] [-i d] [-m d] [-f d] [-j d] [-k d] [-N] [-s] [-l d] [-o <file>] <input> <output>
+
+Perform (multi-scale) low rank matrix completion
+
-+-d perform decomposition instead, ie fully sampled
-+-i iter maximum iterations.
-+-m flags which dimensions are reshaped to matrix columns.
-+-f flags which dimensions to perform multi-scale partition.
-+-j scale block size scaling from one scale to the next one.
-+-k size smallest block size
-+-N add noise scale to account for Gaussian noise.
-+-s perform low rank + sparse matrix completion.
-+-l size perform locally low rank soft thresholding with specified block size.
-+-o out2 summed over all non-noise scales to create a denoised output.
-+-h help
++-d perform decomposition instead, ie fully sampled
++-i iter maximum iterations.
++-m flags which dimensions are reshaped to matrix columns.
++-f flags which dimensions to perform multi-scale partition.
++-j scale block size scaling from one scale to the next one.
++-k size smallest block size
++-N add noise scale to account for Gaussian noise.
++-s perform low rank + sparse matrix completion.
++-l size perform locally low rank soft thresholding with specified block size.
++-o out2 summed over all non-noise scales to create a denoised output.
++-h help
+
+
+--mandelbrot--
+
-+Usage: mandelbrot [-s d] [-n d] [-t f] [-z f] [-r f] [-i f] output
++Usage: mandelbrot [-s d] [-n d] [-t f] [-z f] [-r f] [-i f] <output>
+
+Compute mandelbrot set.
+
++-s size image size
++-n # nr. of iterations
++-t t threshold for divergence
++-z z zoom
++-r r offset real
++-i i offset imag
++-h help
+
-+-s size image size
-+-n # nr. of iterations
-+-t t threshold for divergence
-+-z z zoom
-+-r r offset real
-+-i i offset imag
-+-h help
++
++--measure--
++
++Usage: measure [--mse] [--mse-mag] [--ssim] [--psnr] <reference> <input> [<output>]
++
++
++
++--mse mse
++--mse-mag mse of rss (over coil dim)
++--ssim ssim of rss (over coil dim) and mean over other dims
++--psnr psnr of rss (over coil dim) and mean over other dims
++-h help
+
+
+--mip--
+
-+Usage: mip [-m] [-a] bitmask <input> <output>
++Usage: mip [-m] [-a] bitmask <input> <output>
+
+Maximum (minimum) intensity projection (MIP) along dimensions specified by bitmask.
+
++-m minimum
++-a do absolute value first
++-h help
++
++
++--mnist--
++
++Usage: mnist [-a,--apply] [-t,--train] [-g,--gpu] <input> <weights> <ref/output>
+
-+-m minimum
-+-a do absolute value first
-+-h help
++Trains or applies a MNIST network.
++This network is to demonstrate how a neural network can be implemented in BART.
++
++-a,--apply apply nnet
++-t,--train trains network
++-g,--gpu run on gpu
++-h help
+
+
+--moba--
+
-+Usage: moba [-r ...] [-L ...] [-F ...] [-G ...] [-m d] [-l d] [-i d] [-R f] [-T f] [-j f] [-u f] [-C d] [-s f] [-B f] [-b ...] [-d d] [-f f] [-p <string>] [-J] [-M] [-g] [-I <string>] [-t <string>] [-o f] [-k] [--kfilter-1 ...] [--kfilter-2 ...] [-n] [--fat_spec_0 ...] <kspace> <TI/TE> <output> [<sensitivities>]
++Usage: moba [-r ...] [-L] [-P] [-F] [-G] [--bloch] [-m d] [-l d] [-i d] [-R,--reduction f] [-T f] [-j f] [-u f] [-C d] [-s f] [-B f] [-b f:f] [-d d] [-f f] [-p <file>] [-J] [-M] [-g] [--multi-gpu d] [-I <file>] [-t <file>] [-o f] [--img_dims d:d:d] [-k] [--kfilter-1] [--kfilter-2] [-e f] [--fat_spec_0] [--scale_data f] [--seq ...] [--sim ...] [--other ...] <kspace> <TI/TE> <output> [<sensitivities>]
+
+Model-based nonlinear inverse reconstruction
+
-+
-+-r <T>:A:B:C generalized regularization options (-rh for help)
-+-L T1 mapping using model-based look-locker
-+-F T2 mapping using model-based Fast Spin Echo
-+-G T2* mapping using model-based multiple gradient echo
-+-m model Select the MGRE model from enum { WF = 0, WFR2S, WF2R2S, R2S, PHASEDIFF } [default: WFR2S]
-+-l reg 1/-l2 toggle l1-wavelet or l2 regularization.
-+-i iter Number of Newton steps
-+-R redu reduction factor
-+-T damp damping on temporal frames
-+-j minreg Minimum regu. parameter
-+-u rho ADMM rho [default: 0.01]
-+-C iter inner iterations
-+-s step step size
-+-B bound lower bound for relaxivity
-+-b SMO:SC B0 field: spatial smooth level; scaling [default: 222.; 1.]
-+-d level Debug level
-+-f FOV
-+-p PSF
-+-J Stack frames for joint recon
-+-M Simultaneous Multi-Slice reconstruction
-+-g use gpu
-+-I init File for initialization
-+-t Traj
-+-o os Oversampling factor for gridding [default: 1.25]
-+-k k-space edge filter for non-Cartesian trajectories
-+--kfilter-1 k-space edge filter 1
-+--kfilter-2 k-space edge filter 2
-+-n disable normlization of parameter maps for thresholding
-+--fat_spec_0 select fat spectrum from ISMRM fat-water tool
-+-h help
++-r <T>:A:B:C generalized regularization options (-rh for help)
++-L T1 mapping using model-based look-locker
++-P T1 mapping using reparameterized (M0, R1, alpha) model-based look-locker (TR required!)
++-F T2 mapping using model-based Fast Spin Echo
++-G T2* mapping using model-based multiple gradient echo
++--bloch Bloch model-based reconstruction
++-m model Select the MGRE model from enum { WF = 0, WFR2S, WF2R2S, R2S, PHASEDIFF } [default: WFR2S]
++-l 1/-l2 toggle l1-wavelet or l2 regularization.
++-i iter Number of Newton steps
++-R,--reduction redu reduction factor
++-T damp damping on temporal frames
++-j minreg Minimum regularization parameter
++-u rho ADMM rho [default: 0.01]
++-C iter inner iterations
++-s step step size
++-B bound lower bound for relaxation
++-b SMO:SC B0 field: spatial smooth level; scaling [default: 222.; 1.]
++-d level Debug level
++-f FOV
++-p PSF
++-J Stack frames for joint recon
++-M Simultaneous Multi-Slice reconstruction
++-g use gpu
++--multi-gpu num number of gpus to use
++-I init File for initialization
++-t traj K-space trajectory
++-o os Oversampling factor for gridding [default: 1.]
++--img_dims x:y:z dimensions
++-k k-space edge filter for non-Cartesian trajectories
++--kfilter-1 k-space edge filter 1
++--kfilter-2 k-space edge filter 2
++-e kfilter_strength strength for k-space edge filter [default: 2e-3]
++--fat_spec_0 select fat spectrum from ISMRM fat-water tool
++--scale_data f scaling factor for data
++--seq ... configure sequence parameters
++--sim ... configure simulation parameters
++--other ... configure other parameters
++-h help
+
+
+--mobafit--
+
-+Usage: mobafit [-G ...] [-m d] [-i d] [-p ...] [-g] <TE> <echo images> <parameters>
++Usage: mobafit [-T] [-G] [-D] [-m d] [-i d] [-g] <enc> <echo/contrast images> [<coefficients>]
++
++Pixel-wise fitting of physical signal models.
++
++-T TSE
++-G MGRE
++-D diffusion
++-m model Select the MGRE model from enum { WF = 0, WFR2S, WF2R2S, R2S, PHASEDIFF } [default: WFR2S]
++-i iter Number of IRGNM steps
++-g use gpu
++-h help
++
++
++--morphop--
++
++Usage: morphop [-e] [-d] [-o] [-c] mask_size <binary input> [<binary output>]
++
++Perform morphological operators on binary data with odd mask sizes.
+
-+Pixel-wise fitting of sequence models.
++-e EROSION (default)
++-d DILATION
++-o OPENING
++-c CLOSING
++-h help
+
-+-G MGRE
-+-m model Select the MGRE model from enum { WF = 0, WFR2S, WF2R2S, R2S, PHASEDIFF } [default: WFR2S]
-+-i iter Number of IRGNM steps
-+-p px,py,pz (patch size)
-+-g use gpu
-+-h help
++
++--multicfl--
++
++Usage: multicfl [-s] <cfl>1> ... <cfl>N>
++
++Combine/Split multiple cfl files to one multi-cfl file.
++In normal usage, the last argument is the combined multi-cfl,
++with '-s', the first argument is the multi-cfl that is split up
++
++-s separate
++-h help
+
+
+--nlinv--
+
-+Usage: nlinv [-i d] [-d d] [-c] [-N] [-m d] [-U] [-f f] [-p <string>] [-t <string>] [-I <string>] [-g] [-S] [--lowmem] <kspace> <output> [<sensitivities>]
++Usage: nlinv [-i d] [-d d] [-c] [-N] [-m d] [-U] [-f f] [-p <file>] [-t <file>] [-I <file>] [-g] [-S] [--lowmem] <kspace> <output> [<sensitivities>]
+
+Jointly estimate image and sensitivities with nonlinear
+inversion using {iter} iteration steps. Optionally outputs
+the sensitivities.
+
-+-i iter Number of Newton steps
-+-d level Debug level
-+-c Real-value constraint
-+-N Do not normalize image with coil sensitivities
-+-m nmaps Number of ENLIVE maps to use in reconstruction
-+-U Do not combine ENLIVE maps in output
-+-f FOV restrict FOV
-+-p file pattern / transfer function
-+-t file kspace trajectory
-+-I file File for initialization
-+-g use gpu
-+-S Re-scale image after reconstruction
-+--lowmem Use low-mem mode of the nuFFT
-+-h help
++-i iter Number of Newton steps
++-d level Debug level
++-c Real-value constraint
++-N Do not normalize image with coil sensitivities
++-m nmaps Number of ENLIVE maps to use in reconstruction
++-U Do not combine ENLIVE maps in output
++-f FOV restrict FOV
++-p file pattern / transfer function
++-t file kspace trajectory
++-I file File for initialization
++-g use gpu
++-S Re-scale image after reconstruction
++--lowmem Use low-mem mode of the nuFFT
++-h help
++
++
++--nnet--
++
++Usage: nnet [-a,--apply] [-e,--eval] [-t,--train] [-g,--gpu] [-b,--batch-size d] [-l,--load <file>] [-N,--network ...] [-U,--unet-segm ...] [--train-loss ...] [--valid-loss ...] [--valid-data ...] [-T,--train-algo ...] [--adam ...] [--load-memory] [--export-graph <string>] <input> <weights> <ref/output>
++
++Trains or applies a neural network.
++
++-a,--apply apply nnet
++-e,--eval evaluate nnet
++-t,--train trains network
++-g,--gpu run on gpu
++-b,--batch-size batchsize size of mini batches
++-l,--load <weights-init> load weights for continuing training
++-N,--network ... select neural network
++-U,--unet-segm ... configure U-Net for segmentation
++--train-loss ... configure the training loss
++--valid-loss ... configure the validation loss
++--valid-data ... provide validation data
++-T,--train-algo ... configure general training parmeters
++--adam ... configure Adam
++--load-memory load files into memory
++--export-graph <file.dot> export graph for visualization
++-h help
+
+
+--noise--
+
-+Usage: noise [-s d] [-r] [-n f] <input> <output>
++Usage: noise [-s d] [-r] [-n f] <input> <output>
+
+Add noise with selected variance to input.
+
-+-s random seed initialization
-+-r real-valued input
-+-n variance DEFAULT: 1.0
-+-h help
++-s d random seed initialization
++-r real-valued input
++-n variance DEFAULT: 1.0
++-h help
+
+
+--normalize--
+
-+Usage: normalize flags <input> <output>
++Usage: normalize [-b] flags <input> <output>
+
+Normalize along selected dimensions.
+
-+-h help
++-b l1
++-h help
+
+
+--nrmse--
+
-+Usage: nrmse [-t f] [-s] <reference> <input>
++Usage: nrmse [-t f] [-s] <reference> <input>
+
+Output normalized root mean square error (NRMSE),
+i.e. norm(input - ref) / norm(ref)
+
-+-t eps compare to eps
-+-s automatic (complex) scaling
-+-h help
++-t eps compare to eps
++-s automatic (complex) scaling
++-h help
+
+
+--nufft--
+
-+Usage: nufft [-a] [-i] [-d ...] [-t] [-r] [-c] [-l f] [-P] [-s] [-g] [-1] [--lowmem] <traj> <input> <output>
++Usage: nufft [-a] [-i] [-d d:d:d] [-t] [-r] [-c] [-l f] [-P] [-s] [-g] [-1] [--lowmem] <traj> <input> <output>
+
+Perform non-uniform Fast Fourier Transform.
+
-+-a adjoint
-+-i inverse
-+-d x:y:z dimensions
-+-t Toeplitz embedding for inverse NUFFT
-+-r turn-off Toeplitz embedding for inverse NUFFT
-+-c Preconditioning for inverse NUFFT
-+-l lambda l2 regularization
-+-P periodic k-space
-+-s DFT
-+-g GPU (only inverse)
-+-1 use/return oversampled grid
-+--lowmem Use low-mem mode of the nuFFT
-+-h help
++-a adjoint
++-i inverse
++-d x:y:z dimensions
++-t Toeplitz embedding for inverse NUFFT
++-r turn-off Toeplitz embedding for inverse NUFFT
++-c Preconditioning for inverse NUFFT
++-l lambda l2 regularization
++-P periodic k-space
++-s DFT
++-g GPU (only inverse)
++-1 use/return oversampled grid
++--lowmem Use low-mem mode of the nuFFT
++-h help
++
++
++--onehotenc--
++
++Usage: onehotenc [-r] [-i d] <input> <output>
++
++Transforms class labels to one-hot-encoded classes
++
++
++-r get class label by maximum entry
++-i index select dimension
++-h help
+
+
+--ones--
+
-+Usage: ones dims dim1 ... dimn name
++Usage: ones dims dim1 ... dimN <output>
+
+Create an array filled with ones with {dims} dimensions of size {dim1} to {dimn}.
+
-+-h help
++-h help
+
+
+--pattern--
+
-+Usage: pattern [-s d] <kspace> <pattern>
++Usage: pattern [-s d] <kspace> <pattern>
+
+Compute sampling pattern from kspace
+
-+
-+-s bitmask Squash dimensions selected by bitmask
-+-h help
++-s bitmask Squash dimensions selected by bitmask
++-h help
+
+
+--phantom--
+
-+Usage: phantom [-s d] [-S d] [-k] [-t <string>] [-G ...] [-T ...] [-N d] [-B ...] [-x d] [-g d] [-3] [-b] [-r d] <output>
++Usage: phantom [-s d] [-S d] [-k] [-t <file>] [-G] [-T] [--NIST] [--SONAR] [-N d] [-B] [-x d] [-g d] [-3] [-b] [-r d] [--rotation-angle f] [--rotation-steps d] <output>
+
+Image and k-space domain phantoms.
+
-+-s nc nc sensitivities
-+-S nc Output nc sensitivities
-+-k k-space
-+-t file trajectory
-+-G geometric object phantom
-+-T tubes phantom
-+-N num Random tubes phantom and number
-+-B BART logo
-+-x n dimensions in y and z
-+-g n=1,2 select geometry for object phantom
-+-3 3D
-+-b basis functions for geometry
-+-r seed random seed initialization
-+-h help
++-s nc nc sensitivities
++-S nc Output nc sensitivities
++-k k-space
++-t file trajectory
++-G geometric object phantom
++-T tubes phantom
++--NIST NIST phantom (T2 sphere)
++--SONAR Diagnostic Sonar phantom
++-N num Random tubes phantom and number
++-B BART logo
++-x n dimensions in y and z
++-g n=1,2,3 select geometry for object phantom
++-3 3D
++-b basis functions for geometry
++-r seed random seed initialization
++--rotation-angle [deg] Angle of Rotation
++--rotation-steps Number of rotation steps
++-h help
+
+
+--pics--
+
-+Usage: pics [-l ...] [-r f] [-R ...] [-c] [-s f] [-i d] [-t <string>] [-n] [-N] [-g] [-G d] [-p <string>] [-I ...] [-b d] [-e] [-T <string>] [-W <string>] [-d d] [-O d] [-o f] [-u f] [-C d] [-q f] [-f f] [-m ...] [-w f] [-S] [-L d] [-K] [-B <string>] [-P f] [-a ...] [-M] [-U,--lowmem] <kspace> <sensitivities> <output>
++Usage: pics [-l ...] [-r f] [-R ...] [-c] [-s f] [-i d] [-t <file>] [-n] [-N] [-g] [-G d] [-p <file>] [-I] [-b d] [-e] [-W <file>] [-d d] [-u f] [-C d] [-f f] [-m] [-w f] [-S] [-L d] [-K] [-B <file>] [-P f] [-a] [-M] [-U,--lowmem] [--psf_export <file>] [--psf_import <file>] [--wavelet <string>] <kspace> <sensitivities> <output>
+
+Parallel-imaging compressed-sensing reconstruction.
+
-+-l1/-l2 toggle l1-wavelet or l2 regularization.
-+-r lambda regularization parameter
-+-R <T>:A:B:C generalized regularization options (-Rh for help)
-+-c real-value constraint
-+-s step iteration stepsize
-+-i iter max. number of iterations
-+-t file k-space trajectory
-+-n disable random wavelet cycle spinning
-+-N do fully overlapping LLR blocks
-+-g use GPU
-+-G gpun use GPU device gpun
-+-p file pattern or weights
-+-I select IST
-+-b blk Lowrank block size
-+-e Scale stepsize based on max. eigenvalue
-+-T file (truth file)
-+-W <img> Warm start with <img>
-+-d level Debug level
-+-O rwiter (reweighting)
-+-o gamma (reweighting)
-+-u rho ADMM rho
-+-C iter ADMM max. CG iterations
-+-q cclambda (cclambda)
-+-f rfov restrict FOV
-+-m select ADMM
-+-w val inverse scaling of the data
-+-S re-scale the image after reconstruction
-+-L flags batch-mode
-+-K randshift for NUFFT
-+-B file temporal (or other) basis
-+-P eps Basis Pursuit formulation, || y- Ax ||_2 <= eps
-+-a select Primal Dual
-+-M Simultaneous Multi-Slice reconstruction
-+-U,--lowmem Use low-mem mode of the nuFFT
-+-h help
++
++-l 1/-l2 toggle l1-wavelet or l2 regularization.
++-r lambda regularization parameter
++-R <T>:A:B:C generalized regularization options (-Rh for help)
++-c real-value constraint
++-s step iteration stepsize
++-i iter max. number of iterations
++-t file k-space trajectory
++-n disable random wavelet cycle spinning
++-N do fully overlapping LLR blocks
++-g use GPU
++-G gpun use GPU device gpun
++-p file pattern or weights
++-I select IST
++-b blk Lowrank block size
++-e Scale stepsize based on max. eigenvalue
++-W <img> Warm start with <img>
++-d level Debug level
++-u rho ADMM rho
++-C iter ADMM max. CG iterations
++-f rfov restrict FOV
++-m select ADMM
++-w f inverse scaling of the data
++-S re-scale the image after reconstruction
++-L flags batch-mode
++-K randshift for NUFFT
++-B file temporal (or other) basis
++-P eps Basis Pursuit formulation, || y- Ax ||_2 <= eps
++-a select Primal Dual
++-M Simultaneous Multi-Slice reconstruction
++-U,--lowmem Use low-mem mode of the nuFFT
++--psf_export file Export PSF to file
++--psf_import file Import PSF from file
++--wavelet name wavelet type (haar,dau2,cdf44)
++-h help
+
+
+--pocsense--
+
-+Usage: pocsense [-i d] [-r f] [-l d] <kspace> <sensitivities> <output>
++Usage: pocsense [-i d] [-r f] [-l d] <kspace> <sensitivities> <output>
+
+Perform POCSENSE reconstruction.
+
-+-i iter max. number of iterations
-+-r alpha regularization parameter
-+-l 1/-l2 toggle l1-wavelet or l2 regularization
-+-h help
++-i iter max. number of iterations
++-r alpha regularization parameter
++-l 1/-l2 toggle l1-wavelet or l2 regularization
++-h help
+
+
+--poisson--
+
-+Usage: poisson [-Y d] [-Z d] [-y f] [-z f] [-C d] [-v] [-e] [-s d] <outfile>
++Usage: poisson [-Y d] [-Z d] [-y f] [-z f] [-C d] [-v] [-e] [-s d] <output>
+
+Computes Poisson-disc sampling pattern.
+
-+-Y size size dimension 1
-+-Z size size dimension 2
-+-y acc acceleration dim 1
-+-z acc acceleration dim 2
-+-C size size of calibration region
-+-v variable density
-+-e elliptical scanning
-+-s seed random seed
-+-h help
++-Y size size dimension 1
++-Z size size dimension 2
++-y acc acceleration dim 1
++-z acc acceleration dim 2
++-C size size of calibration region
++-v variable density
++-e elliptical scanning
++-s seed random seed
++-h help
+
+
+--pol2mask--
+
-+Usage: pol2mask [-X d] [-Y d] <poly> <output>
++Usage: pol2mask [-X d] [-Y d] <poly> <output>
+
+Compute masks from polygons.
+
-+-X size size dimension 0
-+-Y size size dimension 1
-+-h help
++-X size size dimension 0
++-Y size size dimension 1
++-h help
+
+
+--poly--
+
-+Usage: poly L N a_0 a_1 ... a_N output
-+
-+Evaluate polynomial p(x) = a_0 + a_1 x + a_2 x^2 ... a_N x^N at x = {0, 1, ... , L - 1} where a_i are floats.
-+
-+-h help
++Usage: poly L N a_1 ... a_N <output>
++
++Evaluate polynomial p(x) = a_1 + a_2 x + a_3 x^2 ... a_(N+1) x^N at x = {0, 1, ... , L - 1} where a_i are floats.
++
++-h help
++
++
++--reconet--
++
++Usage: reconet [-t,--train] [-e,--eval] [-a,--apply] [-g,--gpu] [-l,--load <file>] [-b,--batch-size d] [-I,--iterations d] [-n,--normalize] [-N,--network ...] [--resnet-block ...] [--varnet-block ...] [--unet ...] [--data-consistency ...] [--initial-reco ...] [--shared-weights] [--no-shared-weights] [--shared-lambda] [--no-shared-lambda] [--rss-norm] [--trajectory <file>] [--pattern <file>] [--mask <file>] [--valid-data ...] [--train-loss ...] [--valid-loss ...] [-T,--train-algo ...] [--adam ...] [--iPALM ...] [--load-memory] [--lowmem] [--test] [--export-graph <string>] <kspace> <sensitivities> <weights> <ref/out>
++
++Trains or appplies a neural network for reconstruction.
++
++-t,--train train reconet
++-e,--eval evaluate reconet
++-a,--apply apply reconet
++-g,--gpu run on gpu
++-l,--load <weights-init> load weights for continuing training
++-b,--batch-size d size of mini batches
++-I,--iterations d number of unrolled iterations
++-n,--normalize normalize data with maximum magnitude of adjoint reconstruction
++-N,--network ... select neural network
++--resnet-block ... configure residual block
++--varnet-block ... configure variational block
++--unet ... configure U-Net block
++--data-consistency ... configure data-consistency method
++--initial-reco ... configure initialization
++--shared-weights share weights across iterations
++--no-shared-weights share weights across iterations
++--shared-lambda share lambda across iterations
++--no-shared-lambda share lambda across iterations
++--rss-norm scale output image to rss normalization
++--trajectory <traj> trajectory
++--pattern <pattern> sampling pattern / psf in kspace
++--mask <mask> mask for computation of loss
++--valid-data ... provide validation data
++--train-loss ... configure the training loss
++--valid-loss ... configure the validation loss
++-T,--train-algo ... configure general training parmeters
++--adam ... configure Adam
++--iPALM ... configure iPALM
++--load-memory copy training data into memory
++--lowmem reduce memory usage by checkpointing
++--test very small network for tests
++--export-graph <file.dot> export graph for visualization
++-h help
+
+
+--repmat--
+
-+Usage: repmat dimension repetitions <input> <output>
++Usage: repmat dimension repetitions <input> <output>
+
+Repeat input array multiple times along a certain dimension.
+
-+-h help
++-h help
+
+
+--reshape--
+
-+Usage: reshape flags dim1 ... dimN <input> <output>
++Usage: reshape flags dim1 ... dimN <input> <output>
+
+Reshape selected dimensions.
+
-+
-+-h help
++-h help
+
+
+--resize--
+
-+Usage: resize [-c] dim1 size1 ... dimn sizen <input> <output>
++Usage: resize [-c] dim1 size1 ... dimN sizeN <input> <output>
+
-+Resizes an array along dimensions to sizes by truncating or zero-padding.
++Resizes an array along dimensions to sizes by truncating or zero-padding. Please see doc/resize.txt for examples.
+
-+-c center
-+-h help
++-c center
++-h help
+
+
+--rmfreq--
+
-+Usage: rmfreq [-N d] <traj> <k> <k_cor>
++Usage: rmfreq [-N d] [-M <string>] <traj> <k> <k_cor>
+
+Remove angle-dependent frequency
+
-+
-+-N # Number of harmonics [Default: 5]
-+-h help
++-N # Number of harmonics [Default: 5]
++-M file Contrast modulation file
++-h help
+
+
+--rof--
+
-+Usage: rof <lambda> <flags> <input> <output>
++Usage: rof lambda flags <input> <output>
+
+Perform total variation denoising along dims <flags>.
+
-+-h help
++-h help
+
+
+--roistat--
+
-+Usage: roistat [-b] [-C ...] [-S ...] [-M ...] [-D ...] [-E ...] [-V ...] <roi> <input> [<output>]
++Usage: roistat [-b] [-C] [-S] [-M] [-D] [-E] [-V] <roi> <input> [<output>]
+
+Compute ROI statistics.
+
-+-b Bessel's correction, i.e. 1 / (n - 1)
-+-C voxel count
-+-S sum
-+-M mean
-+-D standard deviation
-+-E energy
-+-V variance
-+-h help
++-b Bessel's correction, i.e. 1 / (n - 1)
++-C voxel count
++-S sum
++-M mean
++-D standard deviation
++-E energy
++-V variance
++-h help
+
+
+--rss--
+
-+Usage: rss bitmask <input> <output>
++Usage: rss bitmask <input> <output>
+
+Calculates root of sum of squares along selected dimensions.
+
-+-h help
++-h help
+
+
+--rtnlinv--
+
-+Usage: rtnlinv [-i d] [-d d] [-c] [-N] [-m d] [-U] [-f f] [-p <string>] [-t <string>] [-I <string>] [-g] [-S] [-T f] [-x ...] <kspace> <output> [<sensitivities>]
++Usage: rtnlinv [-i d] [-d d] [-c] [-N] [-m d] [-U] [-f f] [-p <file>] [-t <file>] [-I <file>] [-g] [-S] [-T f] [-x d:d:d] <kspace> <output> [<sensitivities>]
+
+Jointly estimate a time-series of images and sensitivities with nonlinear
+inversion using {iter} iteration steps. Optionally outputs
+the sensitivities.
+
-+-i iter Number of Newton steps
-+-d level Debug level
-+-c Real-value constraint
-+-N Do not normalize image with coil sensitivities
-+-m nmaps Number of ENLIVE maps to use in reconstruction
-+-U Do not combine ENLIVE maps in output
-+-f FOV restrict FOV
-+-p file pattern / transfer function
-+-t file kspace trajectory
-+-I file File for initialization
-+-g use gpu
-+-S Re-scale image after reconstruction
-+-T temp_damp temporal damping [default: 0.9]
-+-x x:y:z Explicitly specify image dimensions
-+-h help
++-i iter Number of Newton steps
++-d level Debug level
++-c Real-value constraint
++-N Do not normalize image with coil sensitivities
++-m nmaps Number of ENLIVE maps to use in reconstruction
++-U Do not combine ENLIVE maps in output
++-f FOV restrict FOV
++-p file pattern / transfer function
++-t file kspace trajectory
++-I file File for initialization
++-g use gpu
++-S Re-scale image after reconstruction
++-T temp_damp temporal damping [default: 0.9]
++-x x:y:z Explicitly specify image dimensions
++-h help
+
+
+--sake--
+
-+Usage: sake [-i d] [-s f] <kspace> <output>
++Usage: sake [-i d] [-s f] <kspace> <output>
+
+Use SAKE algorithm to recover a full k-space from undersampled
+data using low-rank matrix completion.
+
-+-i iter tnumber of iterations
-+-s size rel. size of the signal subspace
-+-h help
++-i iter number of iterations
++-s size rel. size of the signal subspace
++-h help
+
+
+--saxpy--
+
-+Usage: saxpy scale <input1> <input2> <output>
++Usage: saxpy scale <input1> <input2> <output>
+
+Multiply input1 with scale factor and add input2.
+
-+-h help
++-h help
+
+
+--scale--
+
-+Usage: scale factor <input> <output>
++Usage: scale factor <input> <output>
+
+Scale array by {factor}. The scale factor can be a complex number.
+
-+-h help
++-h help
+
+
+--sdot--
+
-+Usage: sdot <input1> <input2>
++Usage: sdot <input1> <input2>
+
+Compute dot product along selected dimensions.
+
-+-h help
++-h help
+
+
+--show--
+
-+Usage: show [-m] [-d d] [-s <string>] [-f <string>] <input>
++Usage: show [-m] [-d d] [-s <string>] [-f <string>] <input>
+
+Outputs values or meta data.
+
-+-m show meta data
-+-d dim show size of dimension
-+-s sep use <sep> as the separator
-+-f format use <format> as the format. Default: "%%+.6e%%+.6ei"
-+-h help
++-m show meta data
++-d dim show size of dimension
++-s sep use <sep> as the separator
++-f format use <format> as the format. Default: "%%+.6e%%+.6ei"
++-h help
+
+
+--signal--
+
-+Usage: signal [-F ...] [-B ...] [-T ...] [-M ...] [-G ...] [--fat] [-I] [-s] [-0 ...] [-1 ...] [-2 ...] [-3 ...] [-r f] [-e f] [-f f] [-t f] [-n d] [-b d] <basis-functions>
++Usage: signal [-F] [-B] [-T] [-M] [-G] [--fat] [-I] [-s] [-0 f:f:f] [-1 f:f:f] [-2 f:f:f] [-3 f:f:f] [-r f] [-e f] [-f f] [-t f] [-n d] [-b d] [--av-spokes d] <basis-functions>
+
+Analytical simulation tool.
+
-+-F FLASH
-+-B bSSFP
-+-T TSE
-+-M MOLLI
-+-G MGRE
-+--fat Simulate additional fat component.
-+-I inversion recovery
-+-s inversion recovery starting from steady state
-+-0 min:max:N range of off-resonance frequency (Hz)
-+-1 min:max:N range of T1s (s)
-+-2 min:max:N range of T2s (s)
-+-3 min:max:N range of Mss
-+-r TR repetition time
-+-e TE echo time
-+-f FA flip ange
-+-t T1 relax T1 relax period (second) for MOLLI
-+-n n number of measurements
-+-b heart beats number of heart beats for MOLLI
-+-h help
++-F FLASH
++-B bSSFP
++-T TSE
++-M MOLLI
++-G MGRE
++--fat Simulate additional fat component.
++-I inversion recovery
++-s inversion recovery starting from steady state
++-0 min:max:N range of off-resonance frequency (Hz)
++-1 min:max:N range of T1s (s)
++-2 min:max:N range of T2s (s)
++-3 min:max:N range of Mss
++-r TR repetition time
++-e TE echo time
++-f FA flip ange
++-t T1 relax T1 relax period (second) for MOLLI
++-n n number of measurements
++-b heart beats number of heart beats for MOLLI
++--av-spokes d Number of averaged consecutive spokes
++-h help
++
++
++--sim--
++
++Usage: sim [-1,--T1 f:f:f] [-2,--T2 f:f:f] [--ROT] [--ODE] [--STM] [--split-dim] [--seq ...] [--other ...] <signal: Mxy> [<Partial derivatives: dR1, dM0, dR2, dB1>]
++
++simulation tool
++
++-1,--T1 min:max:N range of T1 values
++-2,--T2 min:max:N range of T2 values
++--ROT homogeneously discretized simulation based on rotational matrices
++--ODE full ordinary differential equation solver based simulation (default)
++--STM state-transition matrix based simulation
++--split-dim Split output in x, y, and z dimensional parts
++--seq ... configure sequence parameter
++--other ... configure other parameters
++-h help
+
+
+--slice--
+
-+Usage: slice dim1 pos1 ... dimn posn <input> <output>
++Usage: slice dim1 pos1 ... dimN posN <input> <output>
+
+Extracts a slice from positions along dimensions.
+
-+
-+-h help
++-h help
+
+
+--spow--
+
-+Usage: spow exponent <input> <output>
++Usage: spow exponent <input> <output>
+
+Raise array to the power of {exponent}. The exponent can be a complex number.
+
-+-h help
++-h help
+
+
+--sqpics--
+
-+Usage: sqpics [-l ...] [-r f] [-R ...] [-s f] [-i d] [-t <string>] [-n] [-g] [-p <string>] [-b d] [-e] [-T <string>] [-W <string>] [-d d] [-u f] [-C d] [-f f] [-m ...] [-w f] [-S] <kspace> <sensitivities> <output>
++Usage: sqpics [-l ...] [-r f] [-R ...] [-s f] [-i d] [-t <file>] [-n] [-g] [-p <file>] [-b d] [-e] [-W <file>] [-d d] [-u f] [-C d] [-f f] [-m] [-w f] [-S] <kspace> <sensitivities> <output>
+
+Parallel-imaging compressed-sensing reconstruction.
+
-+-l1/-l2 toggle l1-wavelet or l2 regularization.
-+-r lambda regularization parameter
-+-R <T>:A:B:C generalized regularization options (-Rh for help)
-+-s step iteration stepsize
-+-i iter max. number of iterations
-+-t file k-space trajectory
-+-n disable random wavelet cycle spinning
-+-g use GPU
-+-p file pattern or weights
-+-b blk Lowrank block size
-+-e Scale stepsize based on max. eigenvalue
-+-T file (truth file)
-+-W <img> Warm start with <img>
-+-d level Debug level
-+-u rho ADMM rho
-+-C iter ADMM max. CG iterations
-+-f rfov restrict FOV
-+-m Select ADMM
-+-w val scaling
-+-S Re-scale the image after reconstruction
-+-h help
++-l 1/-l2 toggle l1-wavelet or l2 regularization.
++-r lambda regularization parameter
++-R <T>:A:B:C generalized regularization options (-Rh for help)
++-s step iteration stepsize
++-i iter max. number of iterations
++-t file k-space trajectory
++-n disable random wavelet cycle spinning
++-g use GPU
++-p file pattern or weights
++-b blk Lowrank block size
++-e Scale stepsize based on max. eigenvalue
++-W <img> Warm start with <img>
++-d level Debug level
++-u rho ADMM rho
++-C iter ADMM max. CG iterations
++-f rfov restrict FOV
++-m Select ADMM
++-w val scaling
++-S Re-scale the image after reconstruction
++-h help
+
+
+--squeeze--
+
-+Usage: squeeze <input> <output>
++Usage: squeeze <input> <output>
+
+Remove singleton dimensions of array.
+
-+-h help
++-h help
+
+
+--ssa--
+
-+Usage: ssa [-w d] [-z] [-m d] [-n d] [-r d] [-g d] <src> <EOF> [<S>] [<backprojection>]
++Usage: ssa [-w d] [-z] [-m d] [-n d] [-r d] [-g d] <src> <EOF> [<S>] [<backprojection>]
+
+Perform SSA-FARY or Singular Spectrum Analysis. <src>: [samples, coordinates]
+
-+
-+-w window Window length
-+-z Zeropadding [Default: True]
-+-m 0/1 Remove mean [Default: True]
-+-n 0/1 Normalize [Default: False]
-+-r rank Rank for backprojection. r < 0: Throw away first r components. r > 0: Use only first r components.
-+-g bitmask Bitmask for Grouping (long value!)
-+-h help
++-w window Window length
++-z Zeropadding [Default: True]
++-m 0/1 Remove mean [Default: True]
++-n 0/1 Normalize [Default: False]
++-r rank Rank for backprojection. r < 0: Throw away first r components. r > 0: Use only first r components.
++-g bitmask Bitmask for Grouping (long value!)
++-h help
+
+
+--std--
+
-+Usage: std bitmask <input> <output>
++Usage: std bitmask <input> <output>
+
+Compute standard deviation along selected dimensions specified by the {bitmask}
+
-+-h help
++-h help
+
+
+--svd--
+
-+Usage: svd [-e] <input> <U> <S> <VH>
++Usage: svd [-e] <input> <U> <S> <VH>
+
+Compute singular-value-decomposition (SVD).
+
-+
-+-e econ
-+-h help
++-e econ
++-h help
+
+
+--tgv--
+
-+Usage: tgv <lambda> <flags> <input> <output>
++Usage: tgv lambda flags <input> <output>
+
-+Perform total generalized variation denoising along dims <flags>.
++Perform total generalized variation denoising along dims specified by flags.
+
-+-h help
++-h help
+
+
+--threshold--
+
-+Usage: threshold [-H ...] [-W ...] [-L ...] [-D ...] [-B ...] [-j d] [-b d] lambda <input> <output>
++Usage: threshold [-H] [-W] [-L] [-D] [-B] [-j d] [-b d] lambda <input> <output>
+
+Perform (soft) thresholding with parameter lambda.
+
-+-H hard thresholding
-+-W daubechies wavelet soft-thresholding
-+-L locally low rank soft-thresholding
-+-D divergence-free wavelet soft-thresholding
-+-B thresholding with binary output
-+-j bitmask joint soft-thresholding
-+-b blocksize locally low rank block size
-+-h help
++-H hard thresholding
++-W daubechies wavelet soft-thresholding
++-L locally low rank soft-thresholding
++-D divergence-free wavelet soft-thresholding
++-B thresholding with binary output
++-j bitmask joint soft-thresholding
++-b blocksize locally low rank block size
++-h help
+
+
+--toimg--
+
-+Usage: toimg [-g f] [-c f] [-w f] [-d] [-m] [-W] [-h] <input> <output_prefix>
++Usage: toimg [-g f] [-c f] [-w f] [-d] [-m] [-W] <input> <output prefix>
+
+Create magnitude images as png or proto-dicom.
+The first two non-singleton dimensions will
+be used for the image, and the other dimensions
+will be looped over.
+
-+
-+-g gamma gamma level
-+-c contrast contrast level
-+-w window window level
-+-d write to dicom format (deprecated, use extension .dcm)
-+-m re-scale each image
-+-W use dynamic windowing
-+-h help
++-g gamma gamma level
++-c contrast contrast level
++-w window window level
++-d write to dicom format (deprecated, use extension .dcm)
++-m re-scale each image
++-W use dynamic windowing
++-h help
+
+
+--traj--
+
-+Usage: traj [-x d] [-y d] [-d d] [-e d] [-a d] [-t d] [-m d] [-l] [-g] [-r] [-G] [-H] [-s d] [-D] [-R f] [-q ...] [-Q ...] [-O] [-3] [-c] [-E] [-z ...] [-C <string>] [-V <string>] <output>
++Usage: traj [-x d] [-y d] [-d d] [-e d] [-a d] [-t d] [-m d] [-l] [-g] [-r] [-G] [-H] [-s d] [-D] [-o f] [-R f] [-q f:f:f] [-O] [-3] [-c] [-E] [-z d:d] [-C <file>] <output>
+
+Computes k-space trajectories.
+
-+-x x readout samples
-+-y y phase encoding lines
-+-d d full readout samples
-+-e e number of echoes
-+-a a acceleration
-+-t t turns
-+-m mb SMS multiband factor
-+-l aligned partition angle
-+-g golden angle in partition direction
-+-r radial
-+-G golden-ratio sampling
-+-H halfCircle golden-ratio sampling
-+-s # Tiny GA tiny golden angle
-+-D projection angle in [0,360°), else in [0,180°)
-+-R phi rotate
-+-q delays gradient delays: x, y, xy
-+-Q delays (gradient delays: z, xz, yz)
-+-O correct transverse gradient error for radial tajectories
-+-3 3D
-+-c asymmetric trajectory [DC sampled]
-+-E multi-echo multi-spoke trajectory
-+-z Ref:Acel Undersampling in z-direction.
-+-C file custom_angle file [phi + i * psi]
-+-V file (custom_gdelays)
-+-h help
++-x x readout samples
++-y y phase encoding lines
++-d d full readout samples
++-e e number of echoes
++-a a acceleration
++-t t turns
++-m mb SMS multiband factor
++-l aligned partition angle
++-g golden angle in partition direction
++-r radial
++-G golden-ratio sampling
++-H halfCircle golden-ratio sampling
++-s # Tiny GA tiny golden angle
++-D projection angle in [0,360°), else in [0,180°)
++-o o oversampling factor
++-R phi rotate
++-q delays gradient delays: x, y, xy
++-O correct transverse gradient error for radial tajectories
++-3 3D
++-c asymmetric trajectory [DC sampled]
++-E multi-echo multi-spoke trajectory
++-z Ref:Acel Undersampling in z-direction.
++-C file custom_angle file [phi + i * psi]
++-h help
+
+
+--transpose--
+
-+Usage: transpose dim1 dim2 <input> <output>
++Usage: transpose dim1 dim2 <input> <output>
+
+Transpose dimensions {dim1} and {dim2}.
+
-+-h help
++-h help
+
+
+--twixread--
+
-+Usage: twixread [-x d] [-r d] [-y d] [-z d] [-s d] [-v d] [-c d] [-n d] [-a d] [-A] [-L] [-P] [-M] <dat file> <output>
++Usage: twixread [-x d] [-r d] [-y d] [-z d] [-s d] [-v d] [-c d] [-n d] [-a d] [-A] [-L] [-P] [-M] [-d d] <dat file> <output>
+
+Read data from Siemens twix (.dat) files.
+
-+-x X number of samples (read-out)
-+-r R radial lines
-+-y Y phase encoding steps
-+-z Z partition encoding steps
-+-s S number of slices
-+-v V number of averages
-+-c C number of channels
-+-n N number of repetitions
-+-a A total number of ADCs
-+-A automatic [guess dimensions]
-+-L use linectr offset
-+-P use partctr offset
-+-M MPI mode
-+-h help
++-x X number of samples (read-out)
++-r R radial lines
++-y Y phase encoding steps
++-z Z partition encoding steps
++-s S number of slices
++-v V number of averages
++-c C number of channels
++-n N number of repetitions
++-a A total number of ADCs
++-A automatic [guess dimensions]
++-L use linectr offset
++-P use partctr offset
++-M MPI mode
++-d level Debug level
++-h help
+
+
+--upat--
+
-+Usage: upat [-Y d] [-Z d] [-y d] [-z d] [-c d] output
++Usage: upat [-Y d] [-Z d] [-y d] [-z d] [-c d] <output>
+
+Create a sampling pattern.
+
-+
-+-Y Y size Y
-+-Z Z size Z
-+-y uy undersampling y
-+-z uz undersampling z
-+-c cen size of k-space center
-+-h help
++-Y Y size Y
++-Z Z size Z
++-y uy undersampling y
++-z uz undersampling z
++-c cen size of k-space center
++-h help
+
+
+--var--
+
-+Usage: var bitmask <input> <output>
++Usage: var bitmask <input> <output>
+
+Compute variance along selected dimensions specified by the {bitmask}
+
-+-h help
++-h help
+
+
+--vec--
+
-+Usage: vec val1 val2 ... valN name
++Usage: vec val1 ... valN <output>
+
+Create a vector of values.
+
-+-h help
++-h help
+
+
+--version--
+
-+Usage: version [-t <string>] [-V] [-h]
++Usage: version [-t <string>] [-V]
+
+Print BART version. The version string is of the form
+TAG or TAG-COMMITS-SHA as produced by 'git describe'. It
@@ -1252,26 +1441,25 @@ index 0000000..2650973
+the abbreviated hash of the last commit (SHA). If there
+are local changes '-dirty' is added at the end.
+
-+
-+-t version Check minimum version
-+-V Output verbose info
-+-h help
++-t version Check minimum version
++-V Output verbose info
++-h help
+
+
+--walsh--
+
-+Usage: walsh [-r ...] [-b ...] <input> <output>
++Usage: walsh [-r d:d:d] [-b d:d:d] <input> <output>
+
+Estimate coil sensitivities using walsh method (use with ecaltwo).
+
-+-r cal_size Limits the size of the calibration region.
-+-b block_size Block size.
-+-h help
++-r cal_size Limits the size of the calibration region.
++-b block_size Block size.
++-h help
+
+
+--wave--
+
-+Usage: wave [-r f] [-b d] [-i d] [-s f] [-c f] [-t f] [-e f] [-g] [-f] [-H] [-v] [-w] [-l] <maps> <wave> <kspace> <output>
++Usage: wave [-r f] [-b d] [-i d] [-s f] [-c f] [-t f] [-e f] [-g] [-f] [-H] [-v] [-w] [-l] <maps> <wave> <kspace> <output>
+
+Perform a wave-caipi reconstruction.
+
@@ -1288,35 +1476,38 @@ index 0000000..2650973
+ * kspace - ( wx, sy, sz, nc, 1)
+ * output - ( sx, sy, sz, 1, md)
+
-+-r lambda Soft threshold lambda for wavelet or locally low rank.
-+-b blkdim Block size for locally low rank.
-+-i mxiter Maximum number of iterations.
-+-s stepsz Step size for iterative method.
-+-c cntnu Continuation value for IST/FISTA.
-+-t toler Tolerance convergence condition for iterative method.
-+-e eigvl Maximum eigenvalue of normal operator, if known.
-+-g use GPU
-+-f Reconstruct using FISTA instead of IST.
-+-H Use hogwild in IST/FISTA.
-+-v Split result to real and imaginary components.
-+-w Use wavelet.
-+-l Use locally low rank across the real and imaginary components.
-+-h help
++-r lambda Soft threshold lambda for wavelet or locally low rank.
++-b blkdim Block size for locally low rank.
++-i mxiter Maximum number of iterations.
++-s stepsz Step size for iterative method.
++-c cntnu Continuation value for IST/FISTA.
++-t toler Tolerance convergence condition for iterative method.
++-e eigvl Maximum eigenvalue of normal operator, if known.
++-g use GPU
++-f Reconstruct using FISTA instead of IST.
++-H Use hogwild in IST/FISTA.
++-v Split result to real and imaginary components.
++-w Use wavelet.
++-l Use locally low rank across the real and imaginary components.
++-h help
+
+
+--wavelet--
+
-+Usage: wavelet [-a] flags [dims] <input> <output>
++Usage: wavelet [-a] [-H] [-D] [-C] bitmask [dim1 ... dimN ] <input> <output>
+
+Perform wavelet transform.
+
-+-a adjoint (specify dims)
-+-h help
++-a adjoint (specify dims)
++-H type: Haar
++-D type: Dau2
++-C type: CDF44
++-h help
+
+
+--wavepsf--
+
-+Usage: wavepsf [-c] [-x d] [-y d] [-r f] [-a d] [-t f] [-g f] [-s f] [-n d] <output>
++Usage: wavepsf [-c] [-x d] [-y d] [-r f] [-a d] [-t f] [-g f] [-s f] [-n d] <output>
+
+Generate a wave PSF in hybrid space.
+- Assumes the first dimension is the readout dimension.
@@ -1329,44 +1520,44 @@ index 0000000..2650973
+bart reshape 7 wZ 768 1 128 wZ wZ
+bart fmac wY wZ wYZ
+
-+-c Set to use a cosine gradient wave
-+-x RO_dim Number of readout points
-+-y PE_dim Number of phase encode points
-+-r PE_res Resolution of phase encode in cm
-+-a ADC_T Readout duration in microseconds.
-+-t ADC_dt ADC sampling rate in seconds
-+-g gMax Maximum gradient amplitude in Gauss/cm
-+-s sMax Maximum gradient slew rate in Gauss/cm/second
-+-n ncyc Number of cycles in the gradient wave
-+-h help
++-c Set to use a cosine gradient wave
++-x RO_dim Number of readout points
++-y PE_dim Number of phase encode points
++-r PE_res Resolution of phase encode in cm
++-a ADC_T Readout duration in microseconds.
++-t ADC_dt ADC sampling rate in seconds
++-g gMax Maximum gradient amplitude in Gauss/cm
++-s sMax Maximum gradient slew rate in Gauss/cm/second
++-n ncyc Number of cycles in the gradient wave
++-h help
+
+
+--whiten--
+
-+Usage: whiten [-o <string>] [-c <string>] [-n] <input> <ndata> <output> [<optmat_out>] [<covar_out>]
++Usage: whiten [-o <file>] [-c <file>] [-n] <input> <ndata> <output> [<optmat_out>] [<covar_out>]
+
+Apply multi-channel noise pre-whitening on <input> using noise data <ndata>.
+Optionally output whitening matrix and noise covariance matrix
+
-+-o <optmat_in> use external whitening matrix <optmat_in>
-+-c <covar_in> use external noise covariance matrix <covar_in>
-+-n normalize variance to 1 using noise data <ndata>
-+-h help
++-o <optmat_in> use external whitening matrix <optmat_in>
++-c <covar_in> use external noise covariance matrix <covar_in>
++-n normalize variance to 1 using noise data <ndata>
++-h help
+
+
+--window--
+
-+Usage: window [-H] flags <input> <output>
++Usage: window [-H] flags <input> <output>
+
+Apply Hamming (Hann) window to <input> along dimensions specified by flags
+
-+-H Hann window
-+-h help
++-H Hann window
++-h help
+
+
+--wshfl--
+
-+Usage: wshfl [-R ...] [-b d] [-i d] [-j d] [-s f] [-e f] [-F <string>] [-O <string>] [-t f] [-g] [-K] [-H] [-v] <maps> <wave> <phi> <reorder> <table> <output>
++Usage: wshfl [-R ...] [-b d] [-i d] [-j d] [-s f] [-e f] [-F <file>] [-O <file>] [-t f] [-g] [-K] [-H] [-v] <maps> <wave> <phi> <reorder> <table> <output>
+
+Perform a wave-shuffling reconstruction.
+
@@ -1405,37 +1596,36 @@ index 0000000..2650973
+ * reorder - ( n, 3, 1, 1, 1, 1, 1)
+ * table - ( wx, nc, n, 1, 1, 1, 1)
+
-+-R<T>:A:B:C Generalized regularization options. (-Rh for help)
-+-b blkdim Block size for locally low rank.
-+-i mxiter Maximum number of iterations.
-+-j cgiter Maximum number of CG iterations in ADMM.
-+-s admrho ADMM Rho value.
-+-e eigval Eigenvalue to scale step size. (Optional.)
-+-F frwrd Go from shfl-coeffs to data-table. Pass in coeffs path.
-+-O initl Initialize reconstruction with guess.
-+-t toler Tolerance convergence condition for FISTA.
-+-g Use GPU.
-+-K Go from data-table to shuffling basis k-space.
-+-H Use hogwild.
-+-v Split coefficients to real and imaginary components.
-+-h help
++-R <T>:A:B:C Generalized regularization options. (-Rh for help)
++-b blkdim Block size for locally low rank.
++-i mxiter Maximum number of iterations.
++-j cgiter Maximum number of CG iterations in ADMM.
++-s admrho ADMM Rho value.
++-e eigval Eigenvalue to scale step size. (Optional.)
++-F frwrd Go from shfl-coeffs to data-table. Pass in coeffs path.
++-O initl Initialize reconstruction with guess.
++-t toler Tolerance convergence condition for FISTA.
++-g Use GPU.
++-K Go from data-table to shuffling basis k-space.
++-H Use hogwild.
++-v Split coefficients to real and imaginary components.
++-h help
+
+
+--zeros--
+
-+Usage: zeros dims dim1 ... dimn name
++Usage: zeros dims dim1 ... dimN <output>
+
+Create a zero-filled array with {dims} dimensions of size {dim1} to {dimn}.
+
-+-h help
++-h help
+
+
+--zexp--
+
-+Usage: zexp [-i] <input> <output>
++Usage: zexp [-i] <input> <output>
+
+Point-wise complex exponential.
+
-+
-+-i imaginary
-+-h help
++-i imaginary
++-h help
View it on GitLab: https://salsa.debian.org/med-team/bart/-/commit/33c1e776ad9daf599fb2f8654199593112758ae1
--
View it on GitLab: https://salsa.debian.org/med-team/bart/-/commit/33c1e776ad9daf599fb2f8654199593112758ae1
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