--- name: "ImageMath" section: "1" platform: "linux" package: "ants" version: "2.1.0-5" release: "Debian 9 (Stretch)" platforms: ["linux"] url: "https://new.carta.tech/ImageMath" --- # ImageMath(1) part of ANTS registration suite ## NAME ImageMath - part of ANTS registration suite ## SYNOPSIS **ImageMath** *ImageDimension \* \[*operations and inputs*\] *\ \* ## DESCRIPTION Usage Information - ImageDimension: 2 or 3 (for 2 or 3 dimensional operations). ImageDimension: 4 (for operations on 4D file, e.g. time-series data). Operator: See list of valid operators below. The last two arguments can be an image or float value NB: Some options output text files ### Mathematical Operations: - m : Multiply **---** use vm for vector multiply - \+ : Add **---** use v+ for vector add - \- : Subtract **---** use v- for vector subtract - / : Divide - ^ : Power - max : voxelwise max - exp : Take exponent exp(imagevalue\*value) - addtozero : add image-b to image-a only over points where image-a has zero values - overadd : replace image-a pixel with image-b pixel if image-b pixel is non-zero - abs : absolute value - total : Sums up values in an image or in image1\*image2 (img2 is the probability mask) - mean : Average of values in an image or in image1\*image2 (img2 is the probability mask) - vtotal : Sums up volumetrically weighted values in an image or in image1\*image2 (img2 is the probability mask) - Decision : Computes result=1./(1.+exp(**-1**.0\*( pix1-0.25)/pix2)) - Neg : Produce image negative ### Spatial Filtering: - Project Image1.ext axis-a which-projection : Project an image along axis a, which-projection=0(sum, 1=max, 2=min) - G Image1.ext s : Smooth with Gaussian of sigma = s - MD Image1.ext s : Morphological Dilation with radius s - ME Image1.ext s : Morphological Erosion with radius s - MO Image1.ext s : Morphological Opening with radius s - MC Image1.ext s : Morphological Closing with radius s - GD Image1.ext s : Grayscale Dilation with radius s - GE Image1.ext s : Grayscale Erosion with radius s - GO Image1.ext s : Grayscale Opening with radius s - GC Image1.ext s : Grayscale Closing with radius s - BlobDetector Image1.ext NumberOfBlobsToExtract Optional-Input-Image2 Blob-2-out.nii.gz N-Blobs-To-Match : blob detection by searching for local extrema of the Laplacian of the Gassian (LoG) - Example matching 6 best blobs from 2 images: ImageMath 2 blob.nii.gz BlobDetector image1.nii.gz 1000 image2.nii.gz blob2.nii.gz 6 - MatchBlobs Image1.ext Image1LM.ext Image2.ext Transform Image: Translate InImage.ext x \[ y z \] ### Time Series Operations: - CompCorrAuto : Outputs a csv file containing global signal vector and N comp-corr eigenvectors determined from PCA of the high-variance voxels. Also outputs a comp-corr + global signal corrected 4D image as well as a 3D image measuring the time series variance. Requires a label image with label 1 identifying voxels in the brain. - ImageMath 4 ${out}compcorr.nii.gz ThreeTissueConfounds ${out}.nii.gz ${out}seg.nii.gz 1 3 : Outputs average global, CSF and WM signals. Requires a label image with 3 labels , csf, gm , wm . - Usage : ThreeTissueConfounds 4D\_TimeSeries.nii.gz LabeLimage.nii.gz csf-label wm-label - TimeSeriesSubset : Outputs n 3D image sub-volumes extracted uniformly from the input time-series 4D image. - Usage : TimeSeriesSubset 4D\_TimeSeries.nii.gz n - TimeSeriesDisassemble : Outputs n 3D image volumes for each time-point in time-series 4D image. - Usage : TimeSeriesDisassemble 4D\_TimeSeries.nii.gz - TimeSeriesAssemble : Outputs a 4D time-series image from a list of 3D volumes. - Usage : TimeSeriesAssemble time\_spacing time\_origin \*images.nii.gz - TimeSeriesToMatrix : Converts a 4D image + mask to matrix (stored as csv file) where rows are time and columns are space . - Usage : TimeSeriesToMatrix 4D\_TimeSeries.nii.gz mask - TimeSeriesSimpleSubtraction : Outputs a 3D mean pair-wise difference list of 3D volumes. - Usage : TimeSeriesSimpleSubtraction image.nii.gz - TimeSeriesSurroundSubtraction : Outputs a 3D mean pair-wise difference list of 3D volumes. - Usage : TimeSeriesSurroundSubtraction image.nii.gz - TimeSeriesSincSubtraction : Outputs a 3D mean pair-wise difference list of 3D volumes. - Usage : TimeSeriesSincSubtraction image.nii.gz - SplitAlternatingTimeSeries : Outputs 2 3D time series - Usage : SplitAlternatingTimeSeries image.nii.gz - ComputeTimeSeriesLeverage : Outputs a csv file that identifies the raw leverage and normalized leverage for each time point in the 4D image. leverage, here, is the difference of the time-point image from the average of the n images. the normalized leverage is = average( sum\_k abs(Leverage(t)-Leverage(k)) )/Leverage(t). - Usage : ComputeTimeSeriesLeverage 4D\_TimeSeries.nii.gz k\_neighbors - SliceTimingCorrection : Outputs a slice-timing corrected 4D time series - Usage : SliceTimingCorrection image.nii.gz sliceTiming \[sinc / bspline\] \[sincRadius=4 / bsplineOrder=3\] - PASL : computes the PASL model of CBF f = rac{ lambda DeltaM } - { 2 alpha M\_0 TI\_1 exp( - TI\_2 / T\_{1a} ) } - Usage : PASL 3D/4D\_TimeSeries.nii.gz BoolFirstImageIsControl M0Image parameter\_list.txt - pCASL : computes the pCASL model of CBF f = rac{ lambda DeltaM R\_{1a} } - { 2 alpha M\_0 \[ exp( - w R\_{1a} ) - exp( **-w** ( au + w ) R\_{1a}) \] } - Usage : pCASL 3D/4D\_TimeSeries.nii.gz parameter\_list.txt - PASLQuantifyCBF : Outputs a 3D CBF image in ml/100g/min from a magnetization ratio image - Usage : PASLQuantifyCBF mag\_ratio.nii.gz \[TI1=700\] \[TI2=1900\] \[T1blood=1664\] \[Lambda=0.9\] \[Alpha=0.95\] \[SliceDelay-45\] ### Tensor Operations: - 4DTensorTo3DTensor : Outputs a 3D\_DT\_Image with the same information. - Usage : 4DTensorTo3DTensor 4D\_DTImage.ext - ComponentTo3DTensor : Outputs a 3D\_DT\_Image with the same information as component images. - Usage : ComponentTo3DTensor component\_image\_prefix\[xx,xy,xz,yy,yz,zz\] extension - ExtractComponentFrom3DTensor : Outputs a component images. - Usage : ExtractComponentFrom3DTensor dtImage.ext which={xx,xy,xz,yy,yz,zz} - ExtractVectorComponent: Produces the WhichVec component of the vector - Usage : ExtractVectorComponent VecImage WhichVec - TensorColor : Produces RGB values identifying principal directions - Usage : TensorColor DTImage.ext - TensorFA : - Usage : TensorFA DTImage.ext - TensorFADenominator : - Usage : TensorFADenominator DTImage.ext - TensorFANumerator : - Usage : TensorFANumerator DTImage.ext - TensorIOTest : Will write the DT image back out ... tests I/O processes for consistency. - Usage : TensorIOTest DTImage.ext - TensorMeanDiffusion : Mean of the eigenvalues - Usage : TensorMeanDiffusion DTImage.ext - TensorRadialDiffusion : Mean of the two smallest eigenvalues - Usage : TensorRadialDiffusion DTImage.ext - TensorAxialDiffusion : Largest eigenvalue, equivalent to TensorEigenvalue DTImage.ext 2 - Usage : TensorAxialDiffusion DTImage.ext - TensorEigenvalue : Gets a single eigenvalue 0-2, where 0 = smallest, 2 = largest - Usage : TensorEigenvalue DTImage.ext WhichInd - TensorToVector : Produces vector field identifying one of the principal directions, 2 = largest eigenvalue - Usage : TensorToVector DTImage.ext WhichVec - TensorToVectorComponent: 0 =\> 2 produces component of the principal vector field (largest eigenvalue). 3 = 8 =\> gets values from the tensor - Usage : TensorToVectorComponent DTImage.ext WhichVec - TensorMask : Mask a tensor image, sets background tensors to zero or to isotropic tensors with specified mean diffusivity - Usage : TensorMask DTImage.ext mask.ext \[ backgroundMD = 0 \] - FuseNImagesIntoNDVectorField : Create ND field from N input scalar images - Usage : FuseNImagesIntoNDVectorField imagex imagey imagez ### Label Fusion: - MajorityVoting : Select label with most votes from candidates - Usage: MajorityVoting LabelImage1.nii.gz .. LabelImageN.nii.gz - CorrelationVoting : Select label with local correlation weights - Usage: CorrelationVoting Template.ext IntenistyImages\* LabelImages\* {Optional-Radius=5} - STAPLE : Select label using STAPLE method - Usage: STAPLE confidence-weighting LabelImages\* Note: Gives probabilistic output (float) - MostLikely : Select label from from maximum probabilistic segmentations - Usage: MostLikely probabilityThreshold ProbabilityImages\* - AverageLabels : Select label using STAPLE method - Usage: STAPLE LabelImages\* Note: Gives probabilistic output (float) ### Image Metrics & Info: - PearsonCorrelation: r-value from intesities of two images - Usage: PearsonCorrelation image1.ext image2.ext {Optional-mask.ext} - NeighborhoodCorrelation: local correlations - Usage: NeighborhoodCorrelation image1.ext image2.ext {Optional-radius=5} {Optional-image-mask} - NormalizedCorrelation: r-value from intesities of two images - Usage: NormalizedCorrelation image1.ext image2.ext {Optional-image-mask} - Demons: - Usage: Demons image1.ext image2.ext - Mattes: mutual information - Usage: Mattes image1.ext image2.ext {Optional-number-bins=32} {Optional-image-mask} ### Unclassified Operators: - ReflectionMatrix : Create a reflection matrix about an axis - out.mat ReflectionMatrix image\_in axis - MakeAffineTransform : Create an itk affine transform matrix ClosestSimplifiedHeaderMatrix : does what it says ... image-in, image-out Byte : Convert to Byte image in \[0,255\] - CompareHeadersAndImages: Tries to find and fix header errors. Outputs a repaired image with new header. - Never use this if you trust your header information. - Usage : CompareHeadersAndImages Image1 Image2 - ConvertImageSetToMatrix: Each row/column contains image content extracted from mask applied to images in \*img.nii - Usage : ConvertImageSetToMatrix rowcoloption Mask.nii \*images.nii - ConvertImageSetToMatrix output can be an image type or csv file type. - RandomlySampleImageSetToCSV: N random samples are selected from each image in a list - Usage : RandomlySampleImageSetToCSV N\_samples \*images.nii - RandomlySampleImageSetToCSV outputs a csv file type. - FrobeniusNormOfMatrixDifference: take the difference between two itk-transform matrices and then compute the frobenius norm - Usage : FrobeniusNormOfMatrixDifference mat1 mat2 - ConvertImageSetToEigenvectors: Each row/column contains image content extracted from mask applied to images in \*img.nii - Usage : ConvertImageSetToEigenvectors N\_Evecs Mask.nii \*images.nii - ConvertImageSetToEigenvectors output will be a csv file for each label value \> 0 in the mask. - ConvertImageToFile : Writes voxel values to a file - Usage : ConvertImageToFile imagevalues.nii {Optional-ImageMask.nii} - ConvertLandmarkFile : Converts landmark file between formats. See ANTS.pdf for description of formats. - Usage : ConvertLandmarkFile InFile.txt - Example 1 : ImageMath 3 outfile.vtk ConvertLandmarkFile infile.txt - ConvertToGaussian : - Usage : ConvertToGaussian TValueImage sigma-float - ConvertVectorToImage : The vector contains image content extracted from a mask. Here the vector is returned to its spatial origins as image content - Usage : ConvertVectorToImage Mask.nii vector.nii - CorrelationUpdate : In voxels, compute update that makes Image2 more like Image1. - Usage : CorrelationUpdate Image1.ext Image2.ext RegionRadius - CountVoxelDifference : The where function from IDL - Usage : CountVoxelDifference Image1 Image2 Mask - CorruptImage : - Usage : CorruptImage Image NoiseLevel Smoothing - D : Danielson Distance Transform - MaurerDistance : Maurer distance transform (much faster than Danielson) - Usage : MaurerDistance inputImage {foreground=1} - DiceAndMinDistSum : Outputs DiceAndMinDistSum and Dice Overlap to text log file + optional distance image - Usage : DiceAndMinDistSum LabelImage1.ext LabelImage2.ext OptionalDistImage - EnumerateLabelInterfaces: - Usage : EnumerateLabelInterfaces ImageIn ColoredImageOutname NeighborFractionToIgnore - ClusterThresholdVariate : for sparse estimation - Usage : ClusterThresholdVariate image mask MinClusterSize - ExtractSlice : Extracts slice number from last dimension of volume (2,3,4) dimensions - Usage : ExtractSlice volume.nii.gz slicetoextract - FastMarchingSegmentation: final output is the propagated label image. Optional stopping value: higher values allow more distant propagation - Usage : FastMarchingSegmentation speed/binaryimagemask.ext initiallabelimage.ext Optional-Stopping-Value - FillHoles : Parameter = ratio of edge at object to edge at background; **--** - Parameter = 1 is a definite hole bounded by object only, 0.99 is close Default of parameter \> 1 will fill all holes - Usage : FillHoles Image.ext parameter - InPaint : very simple inpainting **---** assumes zero values should be inpainted - Usage : InPaint #iterations - PeronaMalik : anisotropic diffusion w/varying conductance param (0.25 in example below) - Usage : PeronaMalik image #iterations conductance - Finite : replace non-finite values with finite-value (default = 0) - Usage : Finite Image.exdt {replace-value=0} - FitSphere : - Usage : FitSphere GM-ImageIn {WM-Image} {MaxRad-Default=5} - FlattenImage : Replaces values greater than %ofMax\*Max to the value %ofMax\*Max - Usage : FlattenImage Image %ofMax - GetLargestComponent : Get the largest object in an image - Usage : GetLargestComponent InputImage {MinObjectSize} - Grad : Gradient magnitude with sigma s (if normalize, then output in range \[0, 1\]) - Usage : Grad Image.ext s normalize? - HistogramMatch : - Usage : HistogramMatch SourceImage ReferenceImage {NumberBins-Default=255} {NumberPoints-Default=64} - RescaleImage : - Usage : RescaleImage InputImage min max - WindowImage : - Usage : WindowImage InputImage windowMinimum windowMaximum outputMinimum outputMaximum - NeighborhoodStats : - Usage : NeighborhoodStats inputImage whichStat radius whichStat: 1 = min, 2 = max, 3 = variance, 4 = sigma, 5 = skewness, 6 = kurtosis, 7 = entropy - InvId : computes the inverse-consistency of two deformations and write the inverse consistency error image - Usage : InvId VectorFieldName VectorFieldName - ReplicateDisplacement : replicate a ND displacement to a ND+1 image - Usage : ReplicateDisplacement VectorFieldName TimeDims TimeSpacing TimeOrigin - ReplicateImage : replicate a ND image to a ND+1 image - Usage : ReplicateImage ImageName TimeDims TimeSpacing TimeOrigin - ShiftImageSlicesInTime : shift image slices by one - Usage : ShiftImageSlicesInTime ImageName shift-amount-default-1 shift-dim-default-last-dim - LabelStats : Compute volumes / masses of objects in a label image. Writes to text file - Usage : LabelStats labelimage.ext valueimage.nii - Laplacian : Laplacian computed with sigma s (if normalize, then output in range \[0, 1\]) - Usage : Laplacian Image.ext s normalize? - Canny : Canny edge detector - Usage : Canny Image.ext signa lowerThresh upperThresh - CropBinaryImage : returns cropped image - Lipschitz : Computes the Lipschitz norm of a vector field - Usage : Lipschitz VectorFieldName - MakeImage : - Usage : MakeImage SizeX SizeY {SizeZ}; - MTR : Computes the magnetization transfer ratio ( (M0-M1)/M0 ) and truncates values to \[0,1\] - Usage : MTR M0Image M1Image \[MaskImage\]; - Normalize : Normalize to \[0,1\]. Option instead divides by average value - Usage : Normalize Image.ext opt - PadImage : If Pad-Number is negative, de-Padding occurs - Usage : PadImage ImageIn Pad-Number - SigmoidImage : - Usage : SigmoidImage ImageIn \[alpha=1.0\] \[beta=0.0\] - Sharpen : - Usage : Sharpen ImageIn - CenterImage2inImage1 : - Usage : ReferenceImageSpace ImageToCenter - PH : Print Header - PoissonDiffusion : Solves Poisson's equation in a designated region using non-zero sources - Usage : PoissonDiffusion inputImage labelImage \[sigma=1.0\] \[regionLabel=1\] \[numberOfIterations=500\] \[convergenceThreshold=1e-10\] - PropagateLabelsThroughMask: Final output is the propagated label image. Optional stopping value: higher values allow more distant propagation - Usage : PropagateLabelsThroughMask speed/binaryimagemask.nii.gz initiallabelimage.nii.gz Optional-Stopping-Value 0/1/2 - 0/1/2 \=\> 0, no topology constraint, 1 - strict topology constraint, 2 - no handles - PValueImage : - Usage : PValueImage TValueImage dof - RemoveLabelInterfaces: - Usage : RemoveLabelInterfaces ImageIn - ReplaceVoxelValue: replace voxels in the range \[a,b\] in the input image with c - Usage : ReplaceVoxelValue inputImage a b c - ROIStatistics : computes anatomical locations, cluster size and mass of a stat image which should be in the same physical space (but not nec same resolution) as the label image. - Usage : ROIStatistics LabelNames.txt labelimage.ext valueimage.nii - SetOrGetPixel : - Usage : SetOrGetPixel ImageIn Get/Set-Value IndexX IndexY {IndexZ} - Example 1 : ImageMath 2 outimage.nii SetOrGetPixel Image Get 24 34; Gets the value at 24, 34 - Example 2 : ImageMath 2 outimage.nii SetOrGetPixel Image 1.e9 24 34; This sets 1.e9 as the value at 23 34 - You can also pass a boolean at the end to force the physical space to be used - Segment : Segment an Image with option of Priors, weight 1 =\> maximally local/prior-based ) - Usage : Segment Image1.ext N-Classes LocalityVsGlobalityWeight-In-ZeroToOneRange OptionalPriorImages - stack : Will put 2 images in the same volume - Usage : Stack Image1.ext Image2.ext - ThresholdAtMean : See the code - Usage : ThresholdAtMean Image %ofMean - TileImages : - Usage : TileImages NumColumns ImageList\* - TriPlanarView : - Usage : TriPlanarView ImageIn.nii.gz PercentageToClampLowIntensity PercentageToClampHiIntensity x-slice y-slice z-slice - TruncateImageIntensity: - Usage : TruncateImageIntensity InputImage.ext {lowerQuantile=0.05} {upperQuantile=0.95} {numberOfBins=65} {binary-maskImage} - Where : The where function from IDL - Usage : Where Image ValueToLookFor maskImage-option tolerance