Skip to content
Advanced Normalization Tools (ANTs)
C++ Shell TeX CMake R Perl Other
Branch: master
Clone or download
cookpa Merge pull request #918 from ANTsX/buildMasterAndPRsOnly
COMP: Trying to reduce the Travis overhead by only building master + PRs
Latest commit 2629431 Nov 21, 2019
Type Name Latest commit message Commit time
Failed to load latest commit information.
.github DOC: Updating issue templates Oct 18, 2019
CMake Loosen compiler requirement to gcc-4.8 Oct 27, 2019
Examples COMP: Round 1 Nov 14, 2019
ImageRegistration COMP: Round 8. Nov 1, 2019
ImageSegmentation BUG: Restoring semi-colon at end of warning macro Nov 20, 2019
Scripts BUG: Spaces. Jul 24, 2019
SuperBuild BUG,PERF: Bumping ITK version with fix to N4 stability and small perf… Nov 1, 2019
Temporary COMP: Round 7. Oct 30, 2019
Tensor COMP: Round 1 Nov 14, 2019
Utilities BUG: Restoring semi-colon at end of warning macro Nov 20, 2019
forhtml ENH: add summary tutorial links Mar 16, 2015
.gitignore ENH: Add ignore bin,build directories. Sep 30, 2015
.mailmap FIX: still need that wrong email there Feb 19, 2015
.travis.yml COMP: Trying to reduce the Travis overhead by only building master + PRs Nov 20, 2019
ANTS.cmake COMP: Set default version number to in CMake, and avoid macro… Nov 15, 2019
ANTSCopyright.txt WIP: improving packaging, README, copyright, newAntsExample Jan 18, 2013 COMP: Set default version number to in CMake, and avoid macro… Nov 15, 2019
COPYING.txt WIP: improving packaging, README, copyright, newAntsExample Jan 18, 2013
CTestConfig.cmake ENH: Use existing dashboard. Nov 8, 2018
CTestCustom.cmake COMP: set parameters to v5 in cmake Jun 5, 2018
Common.cmake Fix shared build Sep 27, 2019 Update Sep 24, 2019
README.txt STYLE: Use consistent formatting Dec 18, 2013
SuperBuild.cmake COMP: Set default version number to in CMake, and avoid macro… Nov 15, 2019
Version.cmake Standardize getting version from github tags and sources Sep 15, 2019
_config.yml Set theme jekyll-theme-midnight and migrate Page Generator content Aug 31, 2017
appveyor.yml typo Aug 8, 2017
index.html Update Aug 31, 2017

Advanced Normalization Tools

Build Status

ANTs computes high-dimensional mappings to capture the statistics of brain structure and function. See the collection of examples at this page.

ants template

ANTs allows one to organize, visualize and statistically explore large biomedical image sets.

ants render

ANTs integrates imaging modalities and related information in space and time.

ants render

ANTs works across species or organ systems with minimal customization.

ants primate

ANTs and related tools have won several international and unbiased competitions.

ants competes

ANTsR is the underlying statistical workhorse. ANTsR examples here.

ANTsPy is pythonic ANTs/ANTsR. See this content too.

Questions: Discussion Site or new ANTsDoc or try this version ... also read our guide to evaluation strategies and addressing new problems with ANTs or other software.

The ANTs handout, part of forthcoming ANTs tutorial material here and here.

ANTsTalk - subject to change at any moment

ANTsRegistrationTalk - subject to change at any moment

Install ANTs via pre-built: Packages @ github older versions @ sourceforge ... also, Github Releases are here thanks to Arman Eshaghi. You can also run ANTs Cortical Thickness pipeline in the cloud using the free platform (no installation required).

Build ANTs from: Source-Code (recommended) on Linux / Mac OS or Windows.

ANTs extracts information from complex datasets that include imaging (Word Cloud). Paired with ANTsR (answer), ANTs is useful for managing, interpreting and visualizing multidimensional data. ANTs is popularly considered a state-of-the-art medical image registration and segmentation toolkit. ANTsR is an emerging tool supporting standardized multimodality image analysis. ANTs depends on the Insight ToolKit (ITK), a widely used medical image processing library to which ANTs developers contribute. A summary of some ANTs findings and tutorial material (most of which is on this page) is here.


Brian B. Avants - UPENN

Role: Creator, Algorithm Design, Implementation, more

Nicholas J. Tustison - UVA

Role: Compeller, Algorithm Design, Implementation Guru, more

Hans J. Johnson - UIowa

Role: Large-Scale Application, Testing, Software design

Team Members

Core: Gang Song (Originator), Philip A. Cook, Jeffrey T. Duda (DTI), Ben M. Kandel (Perfusion, multivariate analysis)

Image Registration

Diffeomorphisms: SyN, Independent Evaluation: Klein, Murphy, Template Construction (2004)(2010), Similarity Metrics, Multivariate registration, Multiple modality analysis and statistical bias

Image Segmentation

Atropos Multivar-EM Segmentation (link), Multi-atlas methods (link) and JLF, Bias Correction (link), DiReCT cortical thickness (link), DiReCT in chimpanzees

Multivariate Analysis Eigenanatomy (1) (2)

Prior-Based Eigenanatomy (in prep), Sparse CCA (1), (2), Sparse Regression (link)

ImageMath Useful!

morphology, GetLargestComponent, CCA, FillHoles ... much more!

Application Domains

Frontotemporal degeneration PENN FTD center

Multimodality Neuroimaging

Lung Imaging

  • Structure
  • Perfusion MRI
  • Branching

Multiple sclerosis (lesion filling) example

Background & Theory

ANTs has won several unbiased & international competitions

Learning about ANTs (examples, etc.)






Presentations: e.g. a Prezi about ANTs (WIP)

Reproducible science as a teaching tool: e.g. compilable ANTs tutorial (WIP)

Other examples slideshow

Landmark-based mapping for e.g. hippocampus discussed here

Brief ANTs segmentation video

Benchmarks for expected memory and computation time: results. These results are, of course, system and data dependent.


Google Scholar


Boilerplate ANTs

Here is some boilerplate regarding ants image processing:

We will analyze multiple modality neuroimaging data with Advanced Normalization Tools (ANTs) version >= 2.1 [1] ( ANTs has proven performance in lifespan analyses of brain morphology [1] and function [2] in both adult [1] and pediatric brain data [2,5,6] including infants [7]. ANTs employs both probabilistic tissue segmentation (via Atropos [3]) and machine learning methods based on expert labeled data (via joint label fusion [4]) in order to maximize reliability and consistency of multiple modality image segmentation. These methods allow detailed extraction of critical image-based biomarkers such as volumes (e.g. hippocampus and amygdala), cortical thickness and area and connectivity metrics derived from structural white matter [13] or functional connectivity [12]. Critically, all ANTs components are capable of leveraging multivariate image features as well as expert knowledge in order to learn the best segmentation strategy available for each individual image [3,4]. This flexibility in segmentation and the underlying high-performance normalization methods have been validated by winning several internationally recognized medical image processing challenges conducted within the premier conferences within the field and published in several accompanying articles [8][9][10][11].















ANTs was supported by: R01-EB006266-01 and by K01-ES025432-01

ants chimp

You can’t perform that action at this time.