.\" DO NOT MODIFY THIS FILE!  It was generated by help2man 1.47.5.
.TH ANTSJOINTFUSION "1" "October 2017" "antsJointFusion 2.2.0" "User Commands"
.SH NAME
antsJointFusion \- part of ANTS registration suite
.SH DESCRIPTION
.SS "COMMAND:"
.IP
antsJointFusion
.IP
antsJointFusion 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 implementation
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. Neuroinform., 2013.
.SS "OPTIONS:"
.HP
\fB\-d\fR, \fB\-\-image\-dimensionality\fR 2/3/4
.IP
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.
.TP
\fB\-t\fR, \fB\-\-target\-image\fR targetImage
[targetImageModality0,targetImageModality1,...,targetImageModalityN]
.IP
The target image (or multimodal target images) assumed to be aligned to a common
image domain.
.TP
\fB\-g\fR, \fB\-\-atlas\-image\fR atlasImage
[atlasImageModality0,atlasImageModality1,...,atlasImageModalityN]
.IP
The atlas image (or multimodal atlas images) assumed to be aligned to a common
image domain.
.HP
\fB\-l\fR, \fB\-\-atlas\-segmentation\fR atlasSegmentation
.IP
The atlas segmentation images. For performing label fusion the number of
specified segmentations should be identical to the number of atlas image sets.
.HP
\fB\-a\fR, \fB\-\-alpha\fR 0.1
.IP
Regularization term added to matrix Mx for calculating the inverse. Default =
0.1
.HP
\fB\-b\fR, \fB\-\-beta\fR 2.0
.IP
Exponent for mapping intensity difference to the joint error. Default = 2.0
.HP
\fB\-c\fR, \fB\-\-constrain\-nonnegative\fR (0)/1
.IP
Constrain solution to non\-negative weights.
.TP
\fB\-p\fR, \fB\-\-patch\-radius\fR 2
2x2x2
.IP
Patch radius for similarity measures. Default = 2x2x2
.HP
\fB\-m\fR, \fB\-\-patch\-metric\fR (PC)/MSQ
.IP
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).
.TP
\fB\-s\fR, \fB\-\-search\-radius\fR 3
3x3x3
searchRadiusMap.nii.gz
.IP
Search radius for similarity measures. Default = 3x3x3. One can also specify an
image where the value at the voxel specifies the isotropic search radius at that
voxel.
.HP
\fB\-e\fR, \fB\-\-exclusion\-image\fR label[exclusionImage]
.IP
Specify an exclusion region for the given label.
.HP
\fB\-x\fR, \fB\-\-mask\-image\fR maskImageFilename
.IP
If a mask image is specified, fusion is only performed in the mask region.
.HP
\fB\-o\fR, \fB\-\-output\fR labelFusionImage
.IP
intensityFusionImageFileNameFormat
[labelFusionImage,intensityFusionImageFileNameFormat,<labelPosteriorProbabilityImageFileNameFormat>,<atlasVotingWeightImageFileNameFormat>]
.IP
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.
.HP
\fB\-\-version\fR
.IP
Get version information.
.HP
\fB\-v\fR, \fB\-\-verbose\fR (0)/1
.IP
Verbose output.
.HP
\fB\-h\fR
.IP
Print the help menu (short version).
.HP
\fB\-\-help\fR
.IP
Print the help menu.
<VALUES>: 1