COMMAND:¶

ANTS

OPTIONS:¶

-x, --mask-image maskFileName

this mask -- defined in the 'fixed' image space defines the region of interest over which the registration is computed ==> above 0.1 means inside mask ==> continuous values in range [0.1,1.0] effect optimization like a probability. ==> values > 1 are treated as = 1.0

-m, --image-metric

The metric weights are relative to the weights on the N other metrics passed to ANTS --- N is unlimited. So, the weight, w_i on the i^{th} metric will be w_i=w_i/ ( sum_i w_i ).Intensity-Based Metrics:

CC/cross-correlation/CrossCorrelation[fixedImage,movingImage,weight,radius/OrForMI-#histogramBins] MI/mutual-information/MutualInformation[fixedImage,movingImage,weight,radius/OrForMI-#histogramBins] SMI/spatial-mutual-information/SpatialMutualInformation[fixedImage,movingImage,weight,radius/OrForMI-#histogramBins] PR/probabilistic/Probabilistic[fixedImage,movingImage,weight,radius/OrForMI-#histogramBins] SSD

--- standard intensity difference.[fixedImage,movingImage,weight,radius/OrForMI-#histogramBins]

MSQ/mean-squares/MeanSquares

-- demons-like, radius > 0 uses moving image gradient in metric

deriv.[fixedImage,movingImage,weight,radius/OrForMI-#histogramBins]

Point-Set-Based Metrics:

PSE/point-set-expectation/PointSetExpectation[fixedImage,movingImage,fixedPoints,movingPoints,weight,pointSetPercentage,pointSetSigma,boundaryPointsOnly,kNeighborhood,

PartialMatchingIterations=100000]

the partial matching option assumes the

complete labeling is in the first set of label parameters ... more iterations leads to more symmetry in the matching - 0 iterations means full asymmetry

[fixedImage,movingImage,fixedPoints,movingPoints,weight,pointSetPercentage,pointSetSigma,boundaryPointsOnly,kNeighborhood,alpha,meshResolution,splineOrder,numberOfLevels,useAnisotropicCovariances]

-o, --output-naming

The name for the output - a prefix or a name+type : e.g. -o OUT or -o OUT.nii or -o OUT.mha

--R

TODO/FIXME: the --R sets an ROI option -- it passes a vector of parameters that sets the center and bounding box

of the region of interest for a sub-field

registration. e.g. in 3D the option setting

-r 10x12x15x50x50x25

sets up a

bounding box of size 50,50,25 with origin at 10,12,15 in voxel (should this be physical?) coordinates. <VALUES>: 0

-i, --number-of-iterations

number of iterations per level -- a 'vector' e.g. : 100x100x20 <VALUES>: 10x10x5

--Restrict-Deformation

restrict the gradient that drives the deformation by scalar factors along specified dimensions -- a TReal 'vector' of length ImageDimension to multiply against the similarity metric's gradient values --- e.g. in 3D : 0.1x1x0 --- will set the z gradient to zero and scale the x gradient by 0.1 and y by 1 (no change). Thus, you get a 2.5-Dimensional registration as there is still 3D continuity in the mapping. <VALUES>: 1x1

-v, --verbose

verbose output

--use-all-metrics-for-convergence

enable to use weighted sum of all metric terms for convergence computation. By default, only the first metric is used <VALUES>: 0

-h

Print the help menu (short version). <VALUES>: 0

--help

Print the help menu. <VALUES>: 1, 0

-t, --transformation-model

TRANSFORMATION[gradient-step-length,number-of-time-steps,DeltaTime,symmetry-type].

Choose one of the following TRANSFORMATIONS:

Diff = diffeomorphic Elast =

Elastic

Exp = exponential diff

Greedy Exp = greedy exponential diff, like

diffeomorphic demons. same parameters.

SyN -- symmetric normalization

DeltaTime is the integration time-discretization step - sub-voxel - n-time steps currently fixed at 2 <VALUES>: SyN[0.5]

-r, --regularization

REGULARIZATION[gradient-field-sigma,def-field-sigma,truncation].

Choose one of

the following REGULARIZATIONS:

Gauss = gaussian DMFFD = directly manipulated

free form deformation <VALUES>: Gauss[3,0.5]

-a, --initial-affine

use the input file as the initial affine parameter

-F, --fixed-image-initial-affine

use the input file as the initial affine parameter for the fixed image

--fixed-image-initial-affine-ref-image

reference space for using the input file as the initial affine parameter for the fixed image

-T, --geodesic

= 0 / 1 / 2, 0 = not time-dependent, 1 = asymmetric , 2 = symmetric

-G, --go-faster

true / false -- if true, SyN is faster but loses some accuracy wrt inverse-identity constraint, see Avants MIA 2008. <VALUES>: false

--continue-affine

true (default) | false, do (not) perform affine given the initial affine parameters <VALUES>: true

--number-of-affine-iterations

number of iterations per level -- a 'vector' e.g. : 100x100x20 <VALUES>: 10000x10000x10000

--use-NN

use nearest neighbor interpolation <VALUES>: 0

--use-Histogram-Matching

use histogram matching of moving to fixed image <VALUES>: 0

--affine-metric-type

MI: mutual information (default), MSQ: mean square error, SSD, CC: Normalized correlation, CCH: Histogram-based correlation coefficient (not recommended), GD: gradient difference (not recommended) <VALUES>: MI

--MI-option

option of mutual information: MI_bins x MI_samples (default: 32x32000) <VALUES>: 32x5000

--rigid-affine

use rigid transformation : true / false(default) <VALUES>: false

--do-rigid

use rigid transformation : true / false(default) <VALUES>: false

--affine-gradient-descent-option

option of gradient descent in affine transformation: maximum_step_length x relaxation_factor x minimum_step_length x translation_scales <VALUES>: 0.1x0.5x1.e-4x1.e-4

--use-rotation-header

use rotation matrix in image headers: true (default) / false <VALUES>: false

--ignore-void-origin

ignore the apparently unmatched origins (when use-rotation-header is false and the rotation matrix is identity: true (default) / false <VALUES>: false

--gaussian-smoothing-sigmas

At each resolution level the image is subsampled and smoothed by Gaussian convolution. This option allows the user to override the default smoothing by specifying sigma values (in mm) for smoothing both fixed and moving images for each resolution level. <VALUES>:

--subsampling-factors

At each resolution level the image is subsampled and smoothed by Gaussian convolution. This option allows the user to override the default subsampling by specifying the subsampling factor for both fixed and moving images for each resolution level. <VALUES>: