Utilities

QUIT contains a number of utilities. Note that these are actually compiled in two separate modules - CoreProgs contains the bare minimum of commands for the QUIT tests to run, while the actual Utils modules contains a larger number of useful tools for neuro-imaging pipelines. Their documentation is combined here.

qi affine

This tool applies simple affine transformations to the header data of an image, i.e. rotations or scalings. It was written because of the inconsistent definitions of co-ordinate systems in pre-clinical imaging. Non-primate mammals are usually scanned prone instead of supine, and are quadrupeds instead of bipeds. This means the definitions of superior/inferior and anterior/posterior are different than in clinical scanning. However, several pre-clinical atlases, e.g. Dorr et al, rotate their data so that the clinical conventions apply. It is hence useful as a pre-processing step to adopt the same co-ordinate system. In addition, packages such as SPM or ANTs have several hard-coded assumptions about their input images that are only appropriate for human brains. It can hence be useful to scale up rodent brains by a factor of 10 so that they have roughly human dimensions.

Example Command Line

qi affine input_image.nii.gz --scale=10.0 --rotate=90,0,0

If no output image is specified, the output will be written back to the input filename.

Common Options

  • --scale, -s

    Multiply the voxel spacing by a constant factor. Default is 1.0.

  • --rotate

    Rotate by Euler angles around X,Y,Z axes (degrees). E.g. --rotate=90,0,0 for 90 degrees around X.

  • --trans

    Translate image by X,Y,Z (mm). E.g. --trans=0,0,5.

  • --center, -c

    Set the image origin. Argument must be geo (geometric center) or cog (center of gravity).

  • --permute

    Permute axes in data-space, e.g. 2,0,1. Negative values mean flip as well.

  • --flip

    Flip axes in data-space, e.g. 0,1,0. Occurs after any permutation.

  • --tfm, -t

    Write out the transformation to a file.

qi complex

Manipulate complex/real/imaginary/magnitude/phase data. Created because I was fed up with how fslcomplex works.

Example Command Line

qi complex -m input_magnitude.nii.gz -p input_phase.nii.gz -R output_real.nii.gz -I output_imaginary.nii.gz

Lower case arguments --mag, -m, --pha, -p, --real, -r, --imag, -i, --complex, -x are inputs (of which it is only valid to specify certain combinations, complex OR magnitude/phase OR real/imaginary).

Upper case arguments --MAG, -M, --PHA, -P, --REAL, -R, --IMAG, -I, --COMPLEX, -X are outputs, any or all of which can be specified.

An additional input argument, --realimag (short -l) is for Bruker “complex” data, which consists of all real volumes followed by all imaginary volumes, instead of a true complex datatype. Another input option, --interleaved, is for dcm2niix interleaved real/imaginary data.

The --fixge argument fixes the lack of an FFT shift in the slab direction on GE data by multiplying alternate slices by -1. --negate multiplies the entire volume by -1. --conjugate takes the complex conjugate of the data. --double reads and writes double precision data instead of floats.

qi coil_combine

The command implements both the COMPOSER and Hammond methods for coil combination. For COMPOSER, a wrapper script that includes registration and resampling of low resolution reference data to the image data can be found in qi composer.sh.

Example Command Line

qi coil_combine multicoil_data.nii.gz --composer=composer_reference.nii.gz

Both the input multi-coil file and the reference file must be complex valued. Does not read input from stdin. If a COMPOSER reference file is not specifed, then the Hammond coil combination method is used.

Outputs

  • input_combined.nii.gz - The combined complex-valued image.

Important Options

  • --composer, -c

    Use the COMPOSER method. The reference file should be from a short-echo time reference scan, e.g. UTE or ZTE. If

  • --coils, -C

    Specify the number of coils. Used with the Hammond method. Default is the number of volumes in the input.

  • --region, -r

    The reference region for the Hammond method. Default is an 8x8x8 cube in the center of the acquisition volume.

  • --vol, -V

    Volume to use as reference for the Hammond method. Default is 1.

  • --out, -o

    Add a prefix to output filenames.

References

qi hdr

Prints the header of input files as seen by ITK to stdout. Can extract single header fields or print the entirety.

Example Command Line

qi hdr input_file1.nii.gz input_file2.nii.gz --verbose

Multiple files can be queried at the same time. The --verbose flag will make sure you can tell which is which.

Important Options

If any of the following options are specified, then only those fields will be printed instead of the full header. This is useful if you want to use a header field in a script: * --origin, -o * --direction, -d - Print the image direction/orientation matrix * --spacing, -S - The voxel spacing (optionally specify a single dimension) * --size, -s - The matrix size (optionally specify a single dimension) * --voxvol, -v - The volume of one voxel * --dtype, -T - Print the data type * --dims, -D - Print the number of dimensions * --3D, -3 - Treat input as 3D (discard higher dimensions)

Another useful option is --meta, -m. This will let you query specific image meta-data from the header. You must know the exact name of the meta-data field you wish to obtain.

qi kfilter

MR images often required smoothing or filtering. While this is best done during reconstruction, sometimes it is required as a post-processing step. Instead of filtering by performing a convolution in image space, this tool takes the Fourier Transfrom of input volumes, multiplies k-Space by the specified filter, and transforms back.

Example Command Line

qi kfilter input_file.nii.gz --filter=Gauss,0.5

Outputs

  • input_file_filtered.nii.gz

Important Options

  • --filter,-f

    Specify the filter to use. Default is Tukey. For all filters below the value (r) is the fractional distance from k-Space center, i.e. \(r = \sqrt(((k_x / s_x)^2 + (k_y / s_y)^2 + (k_z / s_z)^2) / 3)\). Valid filters are:

    • Tukey,a,q

      A Tukey filter with parameters a and q. Filter value is 1 for \(r < (1 - a)\) else the value is \(\frac{(1+q)+(1-q)\cos(\pi\frac{r - (1 - a)}{a})}{2}\)

    • Hamming,a,b

      A Hamming filter, parameters a and b, value is \(a - b\cos(\pi(1+r))\)

    • Gauss,w or Gauss,x,y,z

      A Gaussian filter with FWHM specified either isotropically or for each direction independantly.

    • Blackman or Blackman,a

      A Blackman filter, either with the default parameter of \(\alpha=0.16\) or the specified \(\alpha\). Refer to Wikipedia for the relevant equation.

    • Rectangle,Dim,Width,Inside,Outside

      A rectangular or top-hat filter along the specified dimension (must be 0, 1 or 2).

    If multiple filters are specified, they are concatenated, unless the --filter_per_volume option is specified.

  • --filter_per_volume

    For multiple flip-angle data, the difference in contrast between flip-angles can lead to different amounts of ringing. Hence you may wish to filter volumes with more ringing more heavily. If this option is specified, the number of filters on the command line must match the number of volumes in the input file, and they will be processed in order.

  • --complex_in and --complex_out

    Read / write complex data.

  • --zero_pad, -z

    Zero-pad volume by N voxels in each direction. Default is 0.

  • --highpass

    Use a high-pass filter instead of the default low-pass.

  • --save_kernel

    Save filter kernels as images.

  • --save_kspace

    Save k-space before and after filtering.

  • --out, -o

    Change output filename prefix.

qi mask

Implements several different masking strategies. For human data, BET, antsBrainExtraction of 3dSkullStrip are likely better ideas. For pre-clinical data, the strategies below can provide a reasonable mask with some tweaking. There are potentially three stages to generating the mask:

1 - Binary thresholding. If lower or upper thresholds are specified, these are used to separate the image into foreground and background. If neither are specified, then Otsu’s method is used to automatically estimate a reasonable threshold value. 2 - (Optional) Run the RATs algorithm 3 - (Optional) Hole-filling

Example Command Line

qi mask input_image.nii.gz --lower=10 --rats=1200 --fillh=1

In this case an intensity value of 10 will be used as the threshold, RATs will be run with a target volume of 1200 mm^3, and then holes with a radius of 1 voxel will be filled.

Outputs

  • input_image_mask.nii.gz

Important Options

  • --lower,-l/--upper,-u

    Specify lower and/or upper intensity thresholds. Values below/above these values are set to 0, those inside are set 1. If this option is not specified, Otsu’s method will be used to generate a threshold value. If no thresholding is desired, specify --lower=0.

  • --rats, -r

    Use the RATs algorithm to remove non-brain tissue. The RATs algorithm uses erode & dilate filters of progressively increasing size until the largest connected component falls below a target size. For rats, target values of around 1000 mm^3 are reasonable.

  • --fillh, -F

    Fill holes in the mask up to radius N voxels.

  • --out, -o

    Set output filename. Default is input filename with _mask suffix.

  • --vol

    Choose which volume to mask. Default is 0. -1 selects the last volume.

  • --complex, -x

    Input data is complex, take magnitude first before masking.

  • --rats_radius

    Starting radius for the RATS algorithm. Default is 1.

References

qi pca

Denoise a 4D dataset by applying PCA on the time dimension and then retaining a fixed number of Principal Components. See Does et al

Example Command Line

qi pca images.nii.gz --retain=4 --mask=mask.nii.gz

Important Options

  • --retain, -r

    The number of PCs to retain (default 3)

  • --project, -p

    Save the projection of the dataset onto the PCs (basis images) into the specified file

  • --save_pcs, -s

    Save the PCs into the specified JSON file

  • --mask, -m

    Only process voxels within the specified mask.

  • --out, -o

    Change output filename.

Outputs

  • output_pca.nii.gz - The denoised dataset.

qi polyfit/qi polyimg

These tools work together to fit Nth order polynomials to images. This is typically used for smoothing a B1 field.

qi polyfit will output the polynomial co-efficients and origin to stdout. qi polyimg can then read these to generate the polyimage image, using a different image as the reference space. In this way the polynomial image can be created without having to use upsampling.

Example Command Line

qi polyfit noisy_b1_map.nii.gz --mask=brain_mask.nii.gz --order=8 | qi polyimg hires_t1_image.nii.gz hires_smooth_b1_map.nii.gz --order=8

With the above command-line the output of qi polyfit is piped directly to the output of qi polyimg. You can instead redirect it to a file with > and read it in separately. The --order argument must match between the two commands.

Important Options

  • --order, -o

    The order of the fitted polynomial. Default is 4 for qi polyfit and 2 for qi polyimg.

  • --mask, -m

    Only fit the data within a mask. This is usually the brain or only white-matter.

  • --robust, -r (qi polyfit only)

    Use Robust Polynomial Fitting with Huber weights. There is a good discussion of this topic in the Matlab help files.

  • --print-terms (qi polyfit only)

    Print out the polynomial terms.

  • --json (qi polyimg only)

    Read polynomial coefficients from a JSON file instead of stdin.

qi rfprofile

This utility takes a B1+ (transmit field inhomogeneity) map, and reads an excitation slab profile from stdin. The two are multiplied together along the slab direction (default Z), to produce a relative flip-angle or B1 map.

Example Command Line

qi rfprofile b1plus_map.nii.gz output_b1_map.nii.gz < input.json

Example Input File

{
    "rf_pos" : [ -5, 0, 5],
    "rf_vals" : [[0, 1, 0],
                [0, 2, 0]]
}

rf_pos specifies the positions that values of the RF slab have been calculated at, which are specified in rf_vals. Note that rf_vals is an array of arrays - this allows qi rfprofile to calculate profiles for multiple flip-angles in a single pass. The units for rf_pos are the same as image spacing in the header (usually mm). rf_vals is a unitless fraction, relative to the nominal flip-angle.

These values should be generated with a Bloch simulation. Internally, they are used to create a spline to represent the slab profile. This is then interpolated to each voxel’s Z position, and the value multiplied by the input B1+ value at that voxel to produce the output.

Outputs

  • output_b1map.nii.gz - The relative flip-angle/B1 map

Important Options

  • --mask, -m

    Only process voxels within the specified mask.

  • --center, -c

    Set the slab center to the mask center of gravity.

  • --dim

    Which dimension to calculate the profile over. Default is 2 (Z).

  • --subregion, -s

    Process a subregion starting at I,J,K with size SI,SJ,SK.

  • --json

    Read JSON input from a file instead of stdin.

qi ssfp_bands

There are several different methods for removing SSFP bands in the literature. Most of them rely on acquiring multiple SSFP images with different phase-increments (also called phase-cycling or phase-cycling patterns). Changing the phase-increments moves the bands to a different location, after which the images can be combined to reduce the banding. The different approaches are discussed further below, but the recommended method is the Geometric Solution which requires complex data.

Example Command Line

qi ssfp_bands ssfp.nii.gz --method=G --2pass --magnitude

The SSFP file must be complex-valued to use the Geometric Solution or Complex Average methods. For the other methods magnitude data is sufficient. Phase-increments should be in opposing pairs, e.g. 180 & 0 degrees, 90 & 270 degrees. These should either be ordered in two blocks, e.g. 180, 90, 0, 270, or alternating, e.g. 180, 0, 90, 270.

Outputs

The output filename is the input filename with a suffix that will depend on the method selected (see below).

Important Options

  • --method

    Choose the band removal method. Choices are:

    • G Geometric solution. Suffix will be GSL or GSM

    • X` Complex Average. Suffix will be CS (for Complex Solution)

    • R Root-mean-square. Suffix will be RMS

    • M Maximum of magnitudes. Suffix will be Max

    • N Mean of magnitudes. Suffix will be MagMean

  • --regularise

    The Geometric Solution requires regularisation in noisy areas. Available methods are:

    • M Magnitude regularisation as in original paper

    • L Line regularisation (unpublished)

    • N None

    The default is L. If L or M are selected, then that character will be appended to the suffix.

  • --2pass, -2

    Apply the second-pass energy-minimisation filter from the original paper. Can be likened to smoothing the phase data. If selected will append 2 to the suffix.

  • --alt-order

    Phase-increments alternate, e.g. 180, 0, 90, 270. The default is the opposite (two blocks), e.g. 180, 90, 0, 270.

  • --ph-incs

    Number of phase-increments. The default is 4. If you have multiple phase-increments and (for example) multiple flip-angles, qi ssfpbands can process them all in one pass.

  • --ph-order

    The data order is phase-increment varying fastest, flip-angle slowest. The default is the opposite.

  • --magnitude

    Output a magnitude image only.

  • --mask, -m

    Only process voxels within the specified mask. Used with the 2-pass filter.

  • --out, -o

    Change output filename prefix.

References

qi diff

Calculates the mean square difference between two images. Used in the QUIT tests to ensure that calculated parameter maps are close to their baseline values.

Example Command Line

qi diff --baseline=original.nii --input=calculated.nii --noise=0.01

The command returns the dimensionless noise factor on stdout, which is read by the test suite. Note, to make usage clearer, unlike most other QUIT commands all input is specified as arguments.

Important Options

  • --baseline

    The baseline image. Required.

  • --input

    The image to compare to the baseline. Required.

  • --noise

    The added noise level. Default is 0.

  • --abs, -a

    Use absolute difference instead of fractional difference (i.e. do not divide by the baseline image). Useful when images contain genuine zeros (e.g. off resonance maps).

qi newimage

Creates new images filled with specified patterns. Used for generating test data.

Example Command Line

qi newimage --size 32,32,32 --grad_dim 0 --grad_vals 0.5,1.5 output_image.nii.gz

The file specified on the command line is the output file.

Important Options

  • --dims, -d

    The output dimension. Valid values are 3 and 4. Default is 3.

  • --size, -s

    Matrix size of the output image.

  • --fill, -f

    Set all voxels in the image to the specified value.

  • --grad_dim, -g

    The dimension along which to fill with a gradient.

  • --grad_vals, -v

    The low and high values for the gradient, comma-separated. E.g. --grad_vals 0.5,1.5.

  • --steps, -t

    Number of discrete steps for the gradient. Default is 1 (smooth).

  • --spacing, -p

    Voxel spacing, comma-separated for each dimension.

  • --origin, -o

    Image origin, comma-separated.

  • --wrap, -w

    Wrap output voxels at the specified value. Useful for simulating phase data.

qi affine_angle

Calculates the angle between the Z-axis and the transformed Z-axis from one or more transform files. This is useful for verifying the orientation of transform compositions.

Example Command Line

qi affine_angle transform1.tfm transform2.tfm

Multiple transform files can be specified. Prefix a filename with ^ to use the inverse of that transform. All transforms are composed and the resulting angle (in degrees) is printed to stdout.

qi gradient

Calculates the derivative of a 3D image along each axis using itk::DerivativeImageFilter.

Example Command Line

qi gradient input_file.nii.gz

Outputs

Three images are written with suffixes _gradx, _grady, and _gradz.

Important Options

  • --out, -o

    Change output filename prefix.

  • --threads, -T

    Use N threads (default is hardware limit or $QUIT_THREADS).

qi noise_est

Estimates noise statistics from a 4D image within a specified region or mask. Outputs noise mean, standard deviation, and sigma to stdout.

Example Command Line

qi noise_est 4d_file.nii.gz --mask=mask.nii.gz

Either --region or --mask must be specified.

Important Options

  • --region, -r

    Measure noise in the specified region.

  • --mask, -m

    Measure noise within the specified mask.

  • --meansqr

    Return the mean of squared values instead of sigma. Useful for Rician noise correction.

qi select

Selects a set of volumes from a 4D file and writes them to a new 4D file (a reimplemention of fslselectvols).

Example Command Line

qi select in_file.nii out_file.nii 2,4,6,8

The last argument is a comma-separated list of the volumes you wish to select.

qi tgv

Applies Total Generalized Variation denoising.

Example Command Line

qi tgv --alpha=2e-5 image.nii.gz

Important Options

  • --alpha, -a

    The regularization parameter. Default is 1e-5. A value of 2e-5 seems to work well with typical images from a GE scanner.

  • --max_its, -i

    Maximum number of iterations. Default is 16.

  • --thresh

    Threshold for termination. Default is 1e-10.

  • --reduce, -r

    Reduce alpha by this factor. Default is 1.0.

  • --step

    Inverse of step size. Default is 8.0.

  • --complex, -x

    Input is complex valued.

  • --out, -o

    Change output filename.

qi tvmask

Calculate a mask by thresholding the Total Variation in a 4D image.

Example Command Line

qi tvmask images.nii.gz

Important Options

  • --thresh, -t

    The threshold on the TV to define the mask. Default is 2.0.

  • --out, -o

    Change output filename prefix.

  • --threads, -T

    Use N threads (default is hardware limit or $QUIT_THREADS).