README.md

In neuroconductor-devel/ANTsR: ANTs in R: Quantification Tools for Biomedical Images

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ANTsR

DOI 10.17605/osf.io/bsq5v

muschellij2 badges:

A package providing ANTs features in R as well as imaging-specific data representations, spatially regularized dimensionality reduction and segmentation tools. See also the Neuroconductor site.

Description

License: Apache License 2.0

Maintainer: Brian B. Avants

URL: homepage

BugReports: github issues

NeedsCompilation: yes

Travis checks: ANTsR results

Documentation: https://antsx.github.io/ANTsR/.

Preview ANTsR on the cloud

Try the binder link above.

Note: as of this writing, memory is very limited on this cloud preview so some examples may not run successfully.

Downloads

Reference manual: ANTsR

Vignettes:

Wiki: Notes and work in progress examples

Package source: from github

Binaries: here

Windows installation option here

Suggested packages https://github.com/stnava/ANTsRDocker/blob/master/install.R

Install the binary, after downloading, via command line:

R CMD INSTALL ANTsR_*.tgz

Research using ANTsR

• Inter-modality inference yet to be added RIPMMARC

• Eigenanatomy for multiple modality population studies function sparseDecom

• Tumor segmentation function mrvnrfs (not exactly the same but close)

• Multiple modality pediatric template and population study employs several aspects of ANTsR

• Structural networks from subject-level data function makeGraph plus yet to be added RIPMMARC

• SCCAN relating neuroimaging and cognitive batteries function sparseDecom2

• Sparse regression with manifold smoothness constraints function sparseRegression

• Prior-based eigenanatomy function sparseDecom

• Corrective learning for segmentation functions segmentationRefinement.train and segmentationRefinement.predict.

• LINDA: automated segmentation of stroke lesions function mrvnrfs.

• LESYMAP: lesion to symptom mapping function sparseDecom2.

• ANTsRNet A growing collection of well-known deep learning architectures ported to the R language.

  • Image segmentation
    • U-Net (2-D)
    • V-Net (3-D)
  • Image classification
    • AlexNet (2-D, 3-D)
    • Vgg16/Vgg19 (2-D, 3-D)
    • ResNet/ResNeXt (2-D, 3-D)
    • GoogLeNet (2-D)
    • DenseNet (2-D, 3-D)
  • Object detection
    • Single Shot MultiBox Detector (2-D, 3-D)

Installation from source

Please read this entire section before choosing which method you prefer.

In general, these assume you have git installed / accessible in your environment, as well as a compiler, preferably clang. you may also need cmake if you do/can not install cmaker.

Windows users should see Rtools and maybe, also, installr for assistance in setting up their environment for building (must have a compiler too). To my knowledge, there are no recorded instances of ANTsR being installed on Windows. If someone does so, we would like to know.

You will need to install R packages that ANTsR requires. Minimally: Install ITKR and ANTsRCore here and here then do:

mydeps <- c( "Rcpp", "RcppEigen", "magrittr", "rsvd", "magic", "psych" )
install.packages( pkgs = mydeps, dependencies = TRUE )

You can gain additional functionality by installing packages that are listed in the DESCRIPTION file under Suggests. A complete list of recommended ancillary packages here.

Method 1: with devtools in R

library( devtools )
# install_github("stnava/cmaker") # if you do not have cmake
install_github("stnava/ANTsR")

Method 2: from command line (most traditional method)

Assumes git, cmake and compilers are available in your environment (as above).

First, clone the repository:

$ git clone https://github.com/stnava/ITKR.git
$ git clone https://github.com/ANTsX/ANTsRCore.git
$ git clone https://github.com/ANTsX/ANTsR.git

Install the package as follows:

$ R CMD INSTALL ITKR
$ R CMD INSTALL ANTsRCore
$ R CMD INSTALL ANTsR

The travis.yml file also shows a way to install from Linux command line.

Method 3: from binaries

Note that version numbers will change over time.

wget https://github.com/stnava/ITKR/releases/download/latest/ITKR_0.4.12_R_x86_64-pc-linux-gnu.tar.gz
R CMD INSTALL ITKR_0.4.12_R_x86_64-pc-linux-gnu.tar.gz
wget https://github.com/ANTsX/ANTsRCore/releases/download/v0.4.2.1/ANTsRCore_0.4.2.1_R_x86_64-pc-linux-gnu.tar.gz
R CMD INSTALL ANTsRCore_0.4.2.1_R_x86_64-pc-linux-gnu.tar.gz
wget https://github.com/ANTsX/ANTsR/releases/download/latest/ANTsR_0.6_R_x86_64-pc-linux-gnu.tar.gz
R CMD INSTALL ANTsR_0.6_R_x86_64-pc-linux-gnu.tar.gz

Method 4: platform independent via docker and kitematic

This is a beta operation that is in flux but may be convenient for some users.

• based on this approach

• create a docker username

• download and install kitematic

• login to kitematic with your docker username

• search for antsr in the kitematic repository search bar

• create a new container from the stnava version of antsr

• start the container

• type the "access url" address into a browser to run rstudio with antsr. it should be something like http://192.168.99.100:32989/

• you can also add your home folders to the container instance by adjusting the "volumes" option under the settings tab. then you can access local data.

Usage

Load the package:

library(ANTsR)

List the available functions in the namespace ANTsR:

ANTsR::<double-tab>

Call help on a function via ?functionName or see function arguments via args(functionName)

Tagging a beta release

git tag -d beta
git push origin :refs/tags/beta
git tag beta
git push  --tags origin

Release notes

More like development highlights, as opposed to release notes. See git log for the complete history. We try to follow these versioning recommendations for R packages. Under these guidelines, only major.minor is an official release.

0.4.0

• ENH: better compilation and release style.
• ENH: return boolean same size as image
• ENH: improved decomposition methods
• ENH: easier to use antsrSurf and antsrVol

0.3.3

• ENH: spare distance matrix, multi scale svd

0.3.2

• ENH: added domainImg option to plot.antsImage which can standardize plot.

• COMP: test for DVCL define requirement to improve clang and gcc compilations

• WIP: transform objects can be created on the fly and manipulated thanks to jeff duda

• ENH: automation for eigenanatomy

• ENH: reworked SCCAN and eanat

• ENH: mrvnrfs

• ENH: resting state Vignette

• DOC: clarify/extend antsApplyTransforms

• ENH: multidimensional images

• STYLE: iMath not ImageMath in ANTsR

0.3.1

• WIP: iMath improvements

• WIP: ASL pipeline fuctionality

• BUG: Fixed image indexing bug

• BUG: plot.antsImage improvements

• ENH: more antsRegistration options

• ENH: geoSeg

• ENH: JointLabelFusion and JointIntensityFusion

• ENH: Enable negating images

• ENH: weingarten curvature

• ENH: antsApplyTransformsToPoints with example

• ENH: renormalizeProbabilityImages

• ENH: Suppress output from imageWrite.

0.3.0

First official release.

neuroconductor-devel/ANTsR documentation built on April 1, 2021, 1:02 p.m.