sct_dmri_moco

Motion correction of dMRI data. Some of the features to improve robustness were proposed in Xu et al. (https://dx.doi.org/10.1016/j.neuroimage.2012.11.014) and include:

  • group-wise (-g)

  • slice-wise regularized along z using polynomial function (-param). For more info about the method, type: isct_antsSliceRegularizedRegistration

  • masking (-m)

  • iterative averaging of target volume

The outputs of the motion correction process are:

  • the motion-corrected dMRI volumes

  • the time average of the corrected dMRI volumes with b == 0

  • the time average of the corrected dMRI volumes with b != 0

  • a time-series with 1 voxel in the XY plane, for the X and Y motion direction (two separate files), as required for FSL analysis.

  • a TSV file with one row for each time point, with the slice-wise average of the motion correction magnitude for that time point, that can be used for Quality Control.

usage: sct_dmri_moco -i <file> -bvec <file> [-h] [-bval <file>]
                     [-bvalmin <float>] [-g <int>] [-m <file>] [-param <list>]
                     [-x {nn,linear,spline}] [-ofolder <folder>] [-r {0,1}]
                     [-v <int>] [-qc <folder>] [-qc-seg <file>]
                     [-qc-fps <float>] [-qc-dataset <str>] [-qc-subject <str>]

MANDATORY ARGUMENTS

-i

Diffusion data. Example: dmri.nii.gz

-bvec

Bvecs file. Example: bvecs.txt

OPTIONAL ARGUMENTS

-bval

Bvals file. Example: bvals.txt

Default: “”

-bvalmin

B-value threshold (in s/mm2) below which data is considered as b=0. Example: 50.0

Default: 100

-g

Group nvols successive dMRI volumes for more robustness. Example: 2

Default: 3

-m

Binary mask to limit voxels considered by the registration metric. You may also provide a softmask (nonbinary, [0, 1]), and it will be binarized at 0.5. Example: dmri_mask.nii.gz

Default: “”

-param

Advanced parameters. Assign value with =, and separate arguments with ,.

  • poly [int]: Degree of polynomial function used for regularization along Z. For no regularization set to 0. Default=2.

  • smooth [mm]: Smoothing kernel. Default=1.

  • metric {MI, MeanSquares, CC}: Metric used for registration. Default=MI.

  • gradStep [float]: Searching step used by registration algorithm. The higher the more deformation allowed. Default=1.

  • sample [None or 0-1]: Sampling rate used for registration metric. Default=None.

-x

Possible choices: nn, linear, spline

Final interpolation.

Default: “spline”

-ofolder

Output folder. Example: dmri_moco_results

Default: “”

-r

Possible choices: 0, 1

Remove temporary files. 0 = no, 1 = yes

Default: 1

-v

Possible choices: 0, 1, 2

Verbosity. 0: Display only errors/warnings, 1: Errors/warnings + info messages, 2: Debug mode

Default: 1

-qc

The path where the quality control generated content will be saved. (Note: Both -qc and -qc-seg are required in order to generate a QC report.)

-qc-seg

Segmentation of spinal cord to improve cropping in qc report. (Note: Both -qc and -qc-seg are required in order to generate a QC report.)

-qc-fps

This float number is the number of frames per second for the output gif images.

Default: 3

-qc-dataset

If provided, this string will be mentioned in the QC report as the dataset the process was run on.

-qc-subject

If provided, this string will be mentioned in the QC report as the subject the process was run on.