See the new ants website

Installation/Compilation

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Experimental transition to github for development: Wed Jan 23 10:46:13 EST 2013

Release 1.9.x --- final svn release = 1781, now moved to git ....

Introduction -- ANTS is a tool for computational neuroanatomy based on
medical images. ANTS reads any image type that can be read by ITK
(www.itk.org), that is, jpg, tiff, hdr, nii, nii.gz, mha/d and more
image types as well. For the most part, ANTS will output float images
which you can convert to other types with the ANTS
ConvertImagePixelType tool. ImageMath has a bunch of basic utilities
such as multiplication, inversion and many more advanced tools such as
computation of the Lipschitz norm of a deformation field. ANTS
programs may be called from the command line on almost any platform
.... you can compile the code yourself or use the precompiled binaries
for Windows (Vista), OSX (Darwin) or linux (32 bit or 64 bit).
Download the binaries that are correct for you. If you are a naive
user (not from a medical imaging background) then you might still find
the tools here useful. Many of the operations available, for
instance, in PhotoShop are available in ANTS and many more are
available as well. For instance, ANTS tools may be useful in face
mapping / morphing and also in generating animations from two
different images, for instance, interpolating between frames in a
movie. But, mainly, ANTS is useful for brain mapping, segmentation,
measuring cortical thickness and in generating automated or
semi-automated labeling of three-dimensional imagery (e.g. labeling
hippocampus or cortical regions or lobes of the lung). Many
prior-based segmentation possibilities are available in the Atropos
tool, including three tissue segmentation, structure-specific
segmentation and brain extracton.

The ants.pdf file has more details and examples.

New Stuff 1.9.x : Requires git-itk. must be compiled with USE_REVIEW on.

official release of atropos segmentation tool.

checked compilation on windows os.

we now save vector nii.gz files and do not store component images.

improves ImageMath tensor functions.

many operations may be performed on vector images.

some enhancements include:

you can warp a vector field represented as a nii.gz via WarpImageMultiTransform

MeasureMinMaxMean and MultiplyImages support vector images.

the only functionality that we "lost" is the ability to use a bspline interpolator with WIMT. the BSplineInterpolateImageFunction doesnt support vector valued pixels.

Atropos updated and validated.

New Stuff 1.9.2 :

New atropos interface + ROIStatistics in ImageMath

New Stuff 1.9.1 :

Atropos refactored , vtk dependencies allowed , additional tools for surface-based mapping (not much tested), augmented warping for vtk files

Must compile ITK with USE_REVIEW_STATISTICS ON if you want Atropos functionality
Should compile ITK with USE_REVIEW ON
Should compile ITK with USE_OPTIMIZED_REGISTRATION ON
Should have ITK v 3.20 or greater.

New Stuff 1.9 :

Atropos revisions + various utilities.

New Stuff 1.8 :

Sped up CC metric -- comparable to PR but faster.

Fixed the MI metric -- fast and functional.

WarpTimeSeries --- for deforming 4D or vector images.

New Stuff 1.7 :

Now using SymmetricSecondOrderPixelType -- fixes some DT bugs with Nifti I/O etc.

This means our nii tensors have SYMMATRIX as intent (as with standard)

Update in parameters for convergence and inversion -- aids performance.

TensorToVector coloring --- also preliminary integration of vector field

Speed up number one for the CC metric (number two coming later).

Atropos ! new tool for segmentation.

Nick's N4 bias correction tool.

Updates to buildtemplateparallel that allow parallel use on multicore machines.

Various utilities and a few improvements in usage.

New Stuff 1.6 :

Check DT tensor ordering in DTI Read/Write

HistogramMatching in ImageMath

ConvertImagePixelType utility

Affine averaging in buildtemplateparallel

Updated time-dependent diffeomorphic mapping (option --geodesic 1 / 2 ).

Updated with a greedy exponential mapping diffeomorphic approach akin to DiffeomorphicDemons.

Bug fix in checking ANTS convergence.

Other miscellaneous including minor Apocrita changes and allowing spaces in command line interface.

directory guide:

Documentation -- pdf / tex describing ANTS
Examples -- the executable programs and test data in Examples/Data
Scripts -- user-friendly scripts for template building and running studies
Utilities --- basic utilities
ImageRegistration -- base code for ImageRegistration
Temporary -- where temporary code lives
Tensor -- base code for diffusion tensor operations

Use cmake (cmake.org) to set up compilation.
To build ANTS, do the following:

1. get ANTS

svn checkout https://advants.svn.sourceforge.net/svnroot/advants ANTS

1. get itk :

cvs -d :pserver:anoncvs@www.itk.org:/cvsroot/Insight co Insight

1. compile itk and ANTS -- link ANTS to itk build directory

ccmake ANTS/Examples/

1. call ctest in the compile directory and verify that the tests pass

2. in general, to perform a mapping :

include the mask, if desired. mask is inclusive.

ANTS 3 -m PR[tp22_s1.nii,template.nii.gz,1,4] -i 50x20x10 -o tp22map -t SyN[0.25] -x mask.nii.gz -r Gauss[3,0]

The ANTS executable reflects the variational optimization problem

which balances regularization of the transformation model's parameters

and the quality of matchins as driven by a similarity (or data) term

explanation : -m PR -- the similarity metric => PR[fixed.nii,moving,nii,weight,metric-radius]

: -i 50x20 -- the number of iterations and number of resolution levels

: -o tp22map -- the output naming convention (can add an extension)

: -t SyN/Elast/Exp/Syn[time] --- transformation model

: -r Gauss/Bspline -- the regularization models

Gauss[gradient-regularize,deformation-regularize]

: -x mask -- an inclusive mask -- dictates what information to use in registration

-- defined in the fixed domain but works on both domains

: -m other metrics : PSE MSQ MI etc -- some are label-image (or point-set) metrics

and some are intensity metrics

Call ANTS with no params to get detailed help

warp the tp22 to template image

WarpImageMultiTransform 3 tp22_s1.nii tp22totemplate.nii -R template.nii.gz -i tp22mapAffine.txt tp22mapInverseWarp.nii

warp the template image to tp22 -- note reversal of order from above

WarpImageMultiTransform 3 template.nii.gz templatetotp22.nii -R tp22_s1.nii tp22mapWarp.nii tp22mapAffine.txt

or call ants.sh for a standard approach.

use CreateJacobianDeterminantImage to get log-Jacobian (volumetric change) images

and programs StudentsTestOnImages or GLM to peform a statistical study

one might also use SurfaceCurvature to do a curvature study

or LaplacianThickness to do a thickness study

References:

ANTs registration

Principal references
http://www.ncbi.nlm.nih.gov/pubmed/20851191
Avants BB, Tustison NJ, Song G, Cook PA, Klein A, Gee JC.
A reproducible evaluation of ANTs similarity metric performance in brain
image registration.
Neuroimage. 2011 Feb 1;54(3):2033-44. doi: 10.1016/j.neuroimage.2010.09.025.

http://link.springer.com/chapter/10.1007/978-3-642-31340-0_28
Brian B. Avants, Nicholas J. Tustison, Gang Song, Baohua Wu, Michael Stauffer,
Matthew McCormick, Hans J. Johnson, James C. Gee.
A Unified Image Registration Framework for ITK.
Proceedings of the Fifth Workshop on Biomedical Image Registration 2012:266-275.

Symmetric Normalization (SyN)
http://www.ncbi.nlm.nih.gov/pubmed/17659998
Avants BB, Epstein CL, Grossman M, Gee JC.
Symmetric diffeomorphic image registration with cross-correlation: evaluating
automated labeling of elderly and neurodegenerative brain.
Med Image Anal. 2008 Feb;12(1):26-41.

B-spline-based
http://www.ncbi.nlm.nih.gov/pubmed/19171516
Tustison NJ, Avants BB, Gee JC.
Directly manipulated free-form deformation image registration.
IEEE Trans Image Process. 2009 Mar;18(3):624-35. doi: 10.1109/TIP.2008.2010072.

http://link.springer.com/chapter/10.1007%2F978-3-642-31340-0_4
Nicholas J. Tustison, Brian B. Avants:
Diffeomorphic Directly Manipulated Free-Form Deformation Image Registration
via Vector Field Flows.
Proceedings of the Fifth Workshop on Biomedical Image Registration 2012:31-39.

Point set registration
Point-set expectation (PSE)
http://www.ncbi.nlm.nih.gov/pubmed/19437413
Pluta J, Avants BB, Glynn S, Awate S, Gee JC, Detre JA.
Appearance and incomplete label matching for diffeomorphic template based
hippocampus segmentation.
Hippocampus. 2009 Jun;19(6):565-71. doi: 10.1002/hipo.20619.

 Havrda-Charvat-Tsallis (JTB)
 http://www.ncbi.nlm.nih.gov/pubmed/20937578
 Tustison NJ, Awate SP, Song G, Cook TS, Gee JC.
 Point set registration using Havrda-Charvat-Tsallis entropy measures.
 IEEE Trans Med Imaging. 2011 Feb;30(2):451-60. doi: 10.1109/TMI.2010.2086065.

Template construction
http://www.ncbi.nlm.nih.gov/pubmed/15501083
Avants B, Gee JC.
Geodesic estimation for large deformation anatomical shape averaging and interpolation.
Neuroimage. 2004;23 Suppl 1:S139-50.

http://www.ncbi.nlm.nih.gov/pubmed/19818860
Avants BB, Yushkevich P, Pluta J, Minkoff D, Korczykowski M, Detre J, Gee JC.
The optimal template effect in hippocampus studies of diseased populations.
Neuroimage. 2010 Feb 1;49(3):2457-66. doi: 10.1016/j.neuroimage.2009.09.062.

http://www.ncbi.nlm.nih.gov/pubmed/18995188
Avants B, Duda JT, Kim J, Zhang H, Pluta J, Gee JC, Whyte J.
Multivariate analysis of structural and diffusion imaging in traumatic
brain injury.
Acad Radiol. 2008 Nov;15(11):1360-75. doi: 10.1016/j.acra.2008.07.007.

Atropos (n-tissue multivariate segmentation)
http://www.ncbi.nlm.nih.gov/pubmed/21373993
Avants BB, Tustison NJ, Wu J, Cook PA, Gee JC.
An open source multivariate framework for n-tissue segmentation with
evaluation on public data.
Neuroinformatics. 2011 Dec;9(4):381-400. doi: 10.1007/s12021-011-9109-y.

N4 bias correction
http://www.ncbi.nlm.nih.gov/pubmed/20378467
Tustison NJ, Avants BB, Cook PA, Zheng Y, Egan A, Yushkevich PA, Gee JC.
N4ITK: improved N3 bias correction.
IEEE Trans Med Imaging. 2010 Jun;29(6):1310-20. doi: 10.1109/TMI.2010.2046908.

DiReCT aka KellyKapowski/KellySlater
http://www.ncbi.nlm.nih.gov/pubmed/19150502
Das SR, Avants BB, Grossman M, Gee JC.
Registration based cortical thickness measurement.
Neuroimage. 2009 Apr 15;45(3):867-79. doi: 10.1016/j.neuroimage.2008.12.016.

SCCAN
http://www.ncbi.nlm.nih.gov/pubmed/20083207
Avants BB, Cook PA, Ungar L, Gee JC, Grossman M.
Dementia induces correlated reductions in white matter integrity and cortical
thickness: a multivariate neuroimaging study with sparse canonical correlation
analysis.
Neuroimage. 2010 Apr 15;50(3):1004-16. doi: 10.1016/j.neuroimage.2010.01.041.

SurfaceCurvature
http://www.ncbi.nlm.nih.gov/pubmed/15344450
Avants B, Gee J.
The shape operator for differential analysis of images.
Inf Process Med Imaging. 2003 Jul;18:101-13.

Topological well-composedness
http://www.ncbi.nlm.nih.gov/pubmed/21118779
Tustison NJ, Avants BB, Siqueira M, Gee JC.
Topological well-composedness and glamorous glue: a digital gluing algorithm
for topologically constrained front propagation.
IEEE Trans Image Process. 2011 Jun;20(6):1756-61. doi: 10.1109/TIP.2010.2095021.

ANTs-related Studies
http://www.ncbi.nlm.nih.gov/pubmed/15948659
Avants BB, Schoenemann PT, Gee JC.
Lagrangian frame diffeomorphic image registration: Morphometric comparison of
human and chimpanzee cortex.
Med Image Anal. 2006 Jun;10(3):397-412. Epub 2005 Jun 3.

http://www.ncbi.nlm.nih.gov/pubmed/19195496
Klein A, Andersson J, Ardekani BA, Ashburner J, Avants B, Chiang MC,
Christensen GE, Collins DL, Gee J, Hellier P, Song JH, Jenkinson M, Lepage C,
Rueckert D, Thompson P, Vercauteren T, Woods RP, Mann JJ, Parsey RV.
Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI
registration.
Neuroimage. 2009 Jul 1;46(3):786-802. doi: 10.1016/j.neuroimage.2008.12.037.

http://www.ncbi.nlm.nih.gov/pubmed/20123029
Klein A, Ghosh SS, Avants B, Yeo BT, Fischl B, Ardekani B, Gee JC, Mann JJ,
Parsey RV.
Evaluation of volume-based and surface-based brain image registration methods.
Neuroimage. 2010 May 15;51(1):214-20. doi: 10.1016/j.neuroimage.2010.01.091.

http://www.ncbi.nlm.nih.gov/pubmed/23151955
Tustison NJ, Avants BB, Cook PA, Kim J, Whyte J, Gee JC, Stone JR.
Logical circularity in voxel-based analysis: Normalization strategy may induce
statistical bias.
Hum Brain Mapp. 2012 Nov 14. doi: 10.1002/hbm.22211.

http://www.ncbi.nlm.nih.gov/pubmed/17999940
Kim J, Avants B, Patel S, Whyte J, Coslett BH, Pluta J, Detre JA, Gee JC.
Structural consequences of diffuse traumatic brain injury: a large deformation
tensor-based morphometry study.
Neuroimage. 2008 Feb 1;39(3):1014-26. Epub 2007 Oct 13.

gource visualization

gource ./ -s 0.05 --stop-at-end --output-ppm-stream ants.ppm
ffmpeg -y -f image2pipe -vcodec ppm -i ants.ppm -vcodec mpeg4 -preset slow -crf 2 -b:v 4M ./ants_gource.mp4