antsAI(1) part of ANTS registration suite



Program to calculate the optimallinear transform parameters for aligning two images.


-d, --dimensionality 2/3
This option forces the image to be treated as a specified-dimensional image. If not specified, we try to infer the dimensionality from the input image.
-m, --metric MI[fixedImage,movingImage,<numberOfBins=32>,<samplingStrategy={None,Regular,Random}>,<samplingPercentage=[0,1]>]
Mattes[fixedImage,movingImage,<numberOfBins=32>,<samplingStrategy={None,Regular,Random}>,<samplingPercentage=[0,1]>] GC[fixedImage,movingImage,<radius=NA>,<samplingStrategy={None,Regular,Random}>,<samplingPercentage=[0,1]>]
These image metrics are available: MI: joint histogram and Mattes: mutual information and GC: global correlation.
-t, --transform Rigid[gradientStep]
Affine[gradientStep] Similarity[gradientStep]
Several transform options are available. The gradientStep or learningRate characterizes the gradient descent optimization and is scaled appropriately for each transform using the shift scales estimator.
-p, --align-principal-axes
Boolean indicating alignment by principal axes. Alternatively, one can align using blobs (see -b option).
-b, --align-blobs numberOfBlobsToExtract
Boolean indicating alignment by a set of blobs. Alternatively, one can align using blobs (see -p option).
-s, --search-factor searchFactor
Incremental search factor (in degrees) which will sample the arc fraction around the principal axis or default axis.
-c, --convergence numberOfIterations
Number of iterations.
-x, --masks fixedImageMask
Image masks to limit voxels considered by the metric.
-o, --output outputFileName
Specify the output transform (output format an ITK .mat file).
-v, --verbose (0)/1
Verbose output.
Print the help menu (short version).
Print the help menu. <VALUES>: 1