ANTSJOINTTENSORFUSION(1) User Commands ANTSJOINTTENSORFUSION(1)
NAME
antsJointTensorFusion - part of ANTS registration suite
DESCRIPTION
COMMAND:
antsJointTensorFusion
antsJointTensorFusion is an image fusion algorithm developed by Hongzhi Wang and
Paul Yushkevich which won segmentation challenges at MICCAI 2012 and MICCAI 2013.
The original label fusion framework was extended to accommodate intensities by
Brian Avants. This implementation is based on Paul's original ITK-style implementa‐
tion and Brian's ANTsR implementation. References include 1) H. Wang, J. W. Suh, S.
Das, J. Pluta, C. Craige, P. Yushkevich, Multi-atlas segmentation with joint label
fusion IEEE Trans. on Pattern Analysis and Machine Intelligence, 35(3), 611-623,
2013. and 2) H. Wang and P. A. Yushkevich, Multi-atlas segmentation with joint
label fusion and corrective learning--an open source implementation, Front. Neu‐
roinform., 2013.
OPTIONS:
-d, --image-dimensionality 2/3/4
This option forces the image to be treated as a specified-dimensional image. If not
specified, the program tries to infer the dimensionality from the input image.
-t, --target-image targetImage
[targetImageModality0,targetImageModality1,...,targetImageModalityN]
The target image (or multimodal target images) assumed to be aligned to a common
image domain.
-g, --atlas-image atlasImage
[atlasImageModality0,atlasImageModality1,...,atlasImageModalityN]
The atlas image (or multimodal atlas images) assumed to be aligned to a common
image domain.
-l, --atlas-segmentation atlasSegmentation
The atlas segmentation images. For performing label fusion the number of specified
segmentations should be identical to the number of atlas image sets.
-a, --alpha 0.1
Regularization term added to matrix Mx for calculating the inverse. Default = 0.1
-b, --beta 2.0
Exponent for mapping intensity difference to the joint error. Default = 2.0
-r, --retain-label-posterior-images (0)/1
Retain label posterior probability images. Requires atlas segmentations to be spec‐
ified. Default = false
-f, --retain-atlas-voting-images (0)/1
Retain atlas voting images. Default = false
-c, --constrain-nonnegative (0)/1
Constrain solution to non-negative weights.
-u, --log-euclidean (0)/1
Use log Euclidean space for tensor math
-p, --patch-radius 2
2x2x2
Patch radius for similarity measures. Default = 2x2x2
-m, --patch-metric (PC)/MSQ
Metric to be used in determining the most similar neighborhood patch. Options
include Pearson's correlation (PC) and mean squares (MSQ). Default = PC (Pearson
correlation).
-s, --search-radius 3
3x3x3
Search radius for similarity measures. Default = 3x3x3
-e, --exclusion-image label[exclusionImage]
Specify an exclusion region for the given label.
-x, --mask-image maskImageFilename
If a mask image is specified, fusion is only performed in the mask region.
-o, --output labelFusionImage
intensityFusionImageFileNameFormat [labelFusionImage,intensityFusionImageFileName‐
Format,<labelPosteriorProbabilityImageFileNameFormat>,<atlasVotingWeightImageFile‐
NameFormat>]
The output is the intensity and/or label fusion image. Additional optional outputs
include the label posterior probability images and the atlas voting weight images.
--version
Get version information.
-v, --verbose (0)/1
Verbose output.
-h
Print the help menu (short version).
--help
Print the help menu. <VALUES>: 1
antsJointTensorFusion 2.2.0 August 2017 ANTSJOINTTENSORFUSION(1)