COMMAND:¶

antsAI

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

OPTIONS:¶

-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

[numberOfBlobsToExtract,<numberOfBlobsToMatch=numberOfBlobsToExtract>]

Boolean indicating alignment by a set of blobs. Alternatively, one can align using blobs (see -p option).

-s, --search-factor searchFactor

[searchFactor,<arcFraction=1.0>]

Incremental search factor (in degrees) which will sample the arc fraction around the principal axis or default axis.

-c, --convergence numberOfIterations

[numberOfIterations,<convergenceThreshold=1e-6>,<convergenceWindowSize=10>]

Number of iterations.

-x, --masks fixedImageMask

[fixedImageMask,movingImageMask]

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.

-h

Print the help menu (short version).

--help

Print the help menu. <VALUES>: 1