Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
-
○Academic publication links
-
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (13.9%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: neuroconductor-devel
- Language: R
- Default Branch: master
- Size: 21 MB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 1
Metadata Files
README.md
MNITemplate
The goal of MNITemplate is to provide the MNI Template of T1-weighted MRI imaging from http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin2009. In addition to the standard template, the image has been segmented into gray matter, white matter, and cerebrospinal fluid (’CSF’) using the ‘FAST’ algorithm from ‘FSL’ https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FAST..
For a template with a full white-matter parcellation map, see our EveTemplate package.
Creator: Jean-Philippe Fortin, fortin946@gmail.com
Authors and Maintainers: Jean-Philippe Fortin, John Muschelli
Software status
| Resource: | Travis CI |
| ----------- | ---------------------------------------------------------------------------------------------------------------------------------------------------- |
| Platform: | Linux |
| R CMD check | 
|
Table of content
1. Introduction
The MNI152 template that is included with FSL: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Atlases
2. Reading the data into R
We first load the package into R:
{r}
library(MNITemplate)
Once the package is loaded into R, use the command readMNI() to import the MNI template T1-w image as a nifti object into R:
{r}
mni_t1 <- readMNI()
One can use the function orthographic from the oro.nifti package to visualize the template:
{r}
orthographic(mni_t1)
In many preprocessing pipelines, the path of the template file in the system must be specified. For this, use the following:
{r}
mni_path <- getMNIPath()
and to get brain mask:
{r}
mni_brain_mask_path <- getMNIPath("Brain_Mask")
3. Segmentation
We performed a 3-tissue class segmentation of the T1w MNI template using the FSL FAST segmentation algorithm via the fslr package. The script that was used to perform the segmentation can be found here. The segmentation labels are 0 for Background (outside of the brain), 1 for cerebrospinal fluid (CSF), 2 for grey matter (GM) and 3 for white matter (WM). Let's read the segmentation classes into R:
{r}
seg <- readMNISeg()
orthographic(seg)
If one wishes to create a WM mask, could do the following:
{r}
wm_mask <- seg
wm_mask[wm_mask!=3] <- 0
and similarly for the other tissues.
3. Files
| File | Description | Reader |
| ---------------------------------------- | ------------------------------------------------------- | ---------------------------------- |
| MNI152_TI_1mm.nii.gz | T1-w MNI Template, 1mm | readMNI("T1") |
| MNI152_TI_1mm_Brain.nii.gz | T1-w MNI Template, 1mm, skull stripped | readMNI("Brain") |
| MNI152_TI_1mm_Brain_Mask.nii.gz | T1-w MNI Template, 1mm, brain mask | readMNI("Brain_Mask") |
| MNI152_TI_2mm.nii.gz | T1-w MNI Template, 2mm | readMNI("T1", res="2mm") |
| MNI152_TI_2mm_Brain.nii.gz | T1-w MNI Template, 2mm, skull stripped | readMNI("Brain", res="2mm") |
| MNI152_TI_2mm_Brain_Mask.nii.gz | T1-w MNI Template, 2mm, brain mask | readMNI("Brain_Mask", res="2mm") |
| Tissue Segmentation: | | |
| MNI152_TI_1mm_Brain_FAST_seg.nii.gz | FSL FAST tissue classes (1=CSF, 2=GM, 3=WM) for 1mm res | readMNISeg() |
| MNI152_TI_2mm_Brain_FAST_seg.nii.gz | FSL FAST tissue classes (1=CSF, 2=GM, 3=WM) for 2mm res | readMNISeg(res="2mm") |
Owner
- Name: Neuroconductor Development
- Login: neuroconductor-devel
- Kind: organization
- Repositories: 1
- Profile: https://github.com/neuroconductor-devel
Citation (CITATION.bib)
@article{fonov2011unbiased,
title={Unbiased average age-appropriate atlases for pediatric studies},
author={Fonov, Vladimir and Evans, Alan C and Botteron, Kelly and Almli, C Robert and McKinstry, Robert C and Collins, D Louis and Brain Development Cooperative Group and others},
journal={NeuroImage},
volume={54},
number={1},
pages={313--327},
year={2011},
publisher={Elsevier}
}
@article{fonov2009unbiased,
title={Unbiased nonlinear average age-appropriate brain templates from birth to adulthood},
author={Fonov, Vladimir S and Evans, Alan C and McKinstry, Robert C and Almli, CR and Collins, DL},
journal={NeuroImage},
volume={47},
pages={S102},
year={2009},
publisher={Academic Press}
}
@inproceedings{collins1999animal,
title={ANIMAL+ INSECT: improved cortical structure segmentation},
author={Collins, D Louis and Zijdenbos, Alex P and Baar{\'e}, Wim FC and Evans, Alan C},
booktitle={Biennial International Conference on Information Processing in Medical Imaging},
pages={210--223},
year={1999},
organization={Springer}
}
GitHub Events
Total
- Release event: 2
- Push event: 2
- Create event: 2
Last Year
- Release event: 2
- Push event: 2
- Create event: 2
Dependencies
- actions/cache v4 composite
- actions/checkout v4 composite
- actions/upload-artifact master composite
- adigherman/actions/delete-release-by-tag master composite
- adigherman/actions/get-release-asset master composite
- adigherman/actions/get-repo-name master composite
- adigherman/actions/get-repo-version master composite
- adigherman/actions/install-sysdeps-linux master composite
- adigherman/actions/install-sysdeps-macos master composite
- adigherman/actions/install-sysdeps-windows master composite
- coverallsapp/github-action v2 composite
- msys2/setup-msys2 v2 composite
- r-lib/actions/setup-pandoc v2 composite
- r-lib/actions/setup-r v2 composite
- r-lib/actions/setup-r-dependencies v2 composite
- r-lib/actions/setup-tinytex v2 composite
- softprops/action-gh-release v2 composite
- actions/checkout v4 composite
- r-lib/actions/setup-pandoc v2 composite
- r-lib/actions/setup-r v2 composite
- oro.nifti * imports
- covr * suggests
- testthat * suggests