• R
• SAS / Stata
• Matlab
• Python

• R
• Matlab (e.g. SPM)
• Python
• bash (e.g. FSL)

(note SAS/Stata do not exist in this domain)

• Free, open-source
• Cross-platform
• Over 10000 packages
• Taught by stat/biostat departments
• Packaging system is good (well-documented, tested, doable)
• RStudio
• (I know R)

• centralized bioinformatics/genomics packages
• large community/number of packages (> 1300)
• published tutorials and workflows
• additional requirements to CRAN (e.g. packages need vignettes)

• team of developers/maintainers
• multiple grants of support

• integrates multiple neuroimaging software
• standardizes the syntax
• provides workflows
• allows the user to take advantage of all of Python
  • pandas, scikit-learn, Jupyter notebooks

https://imgflip.com/memegenerator/Grandma-Finds-The-Internet

1. A community of developers and users of R packages for imaging
2. A website https://neuroconductor.org/.
   • with tutorials and help
3. A team helping developers and users (John, Adi Gherman, Ciprian Crainiceanu, Brian Caffo)
4. A centralized repository of maintained packages

Carp, Joshua. "The secret lives of experiments: methods reporting in the fMRI literature." Neuroimage 63.1 (2012): 289-300.

• fslr package - call FSL from R

• Requires FSL to be installed and in PATH
  • FSL only available on Unix-style systems

ANTs: Advanced Normalization Tools

• State-of-the-art image processing pipelines
• Built at UPenn under Brian Avants
  • Group has won challenges for imaging analysis
• Still actively maintained and developed
• Depends on the Insight ToolKit (ITK) medical image processing library

• Group tried to wrap C++ code with Rcpp for it to work "seamlessly" with R
• Had some issues with CRAN
• Most developers response: "just make it work"
• NOT like fslr - this built the libraries and could be called using .Call
  • possible (not yet) to use on Windows

• ANTsR depends on CMake:
• ANTsR also depends on ITKR - large code base
• External dependencies are not always welcome
• CRAN response: (more or less)

• We would like more stringent checks than CRAN (like vignettes) like Bioconductor
• But also more lenient ones
• Examples may take > 5 seconds to compile
• Time to build package may take a while
• May not work on Windows if not applicable

Medical images are big (> 5 mb) compared to code

CRAN doesn't like this

• Example data packages are harder to get passed
• We got kirby21.t1 and kirby21.fmri, but they have an implicit downloader function in the code
• Necessary for testing code examples in imaging
• STANDARDIZED file location (system.file)

• Git version control system: stores changes of files

• GitHub is an online server of repositories

• Distribute packages and install them via devtools::install_github

• Builds and checks R packages on Windows (Appveyor) and Linux/OS X (Travis CI)
• Works well with GitHub

• GitHub allows the Neuroconductor team to help fix issues
• Standardized ANTsR checking for NeuroC
• Pull Requests to Group ICA package (Brian Caffo)
• Remove unnecessary hurdles for developers

• dcm2nii by Dr. Chris Rorden
  • jackknife for almost any DICOM type to NIfTI
• dcm2niir wraps a binary executable of dcm2nii
  • calls the command prompt (not always Windows-friendly)
• divest wraps the background C++ code of dcm2nii
  • runs in "native" R

• Allows you to download data from Human Connectome Project
• The 1200 Subjects release: behavioral and 3T MR imaging data from 1206 healthy young adult participants. Standardized protocol.
• Tutorial: http://johnmuschelli.com/neuroc/neurohcp

• Wraps some MATLAB code to call SPM scripts
• Built from SPM batch commands
• spm12_slice_timing, spm12_realign
• spm12_coregister, spm12_segment
• spm12_normalize, spm12_smooth
• http://johnmuschelli.com/neuroc/fmri_analysis_spm12r/index.html

• Wraps Camino Diffusion MRI Toolkit
• Takes in b-values, b-vectors, and tensors
• Fits models for DTI data
• http://johnmuschelli.com/neuroc/DTI_analysis_rcamino/index.html

• Wraps ANTsR functions for nifti objects (from oro.nifti)
• malf function - performs a basic MALF algorithm
• within_visit_registration - performs within-visit registration for structural MRI
• preprocess_mri_within - pipeline to process within-visit sMRI

• Data from the MICCAI 2012 Challenge on Multi-atlas Labelling Data
• From OASIS project and the labeled data as provided by Neuromorphometrics, Inc. (http://Neuromorphometrics.com/)
• Have T1-weighted image, brain mask, image with mask applied, substructure segmentation
  • Hand segmented structures - useful for multi-atlas label fusion (MALF)

Provide an installer to download the current packages:

source("https://neuroconductor.org/neurocLite.R")
neurocLite("kirby21.fmri")
neurocLite("neurobase")
neurocLite("ANTsR")

library(kirby21.t1) # load T1 data
library(kirby21.fmri) # load fMRI data
library(kirby21.base) # helper package to download data
library(neurobase) # neuroconductor base package
fnames = get_image_filenames_list(
  modalities = c("fMRI", "T1"), id = 113, visit = 1)
print(fnames)
t1_fname = fnames$T1 
fmri_fname = fnames$fMRI

                                                 fMRI 
"library/kirby21.fmri/visit_1/113/113-01-fMRI.nii.gz" 
                                                   T1 
    "library/kirby21.t1/visit_1/113/113-01-T1.nii.gz" 

• F1000 R packages channel - get publication for workflow
• Removing dupliate packages from CRAN - like Bioconductor
• Docker image for Neuroconductor:
  • have all dependencies/external software in one container

http://johnmuschelli.com/imaging_in_r/index.html

Example MPRAGE T1 image can be found at http://bit.ly/pittimg

Download the .R file http://bit.ly/pittscript

fMRI in Shiny http://bit.ly/shinybrain

Papaya Example http://bit.ly/pittpapaya