README.md

In Jfortin1/MNITemplate: MNI MRI Template

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, [e-mail]

Authors and Maintainers: Jean-Philippe Fortin, John Muschelli

Software status

| Resource: | Travis CI | | ----------- | ---------------------------------------------------------------------------------------------------------------------------------------------------- | | Platform: | Linux | | R CMD check | |

Table of content

• 1. Introduction
• 2. Reading the data into R
• 3. Files

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:

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:

mni_t1 <- readMNI()

One can use the function orthographic from the oro.nifti package to visualize the template:

orthographic(mni_t1)

In many preprocessing pipelines, the path of the template file in the system must be specified. For this, use the following:

mni_path <- getMNIPath()

and to get brain mask:

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](https://github.com/Jfortin1/MNITemplate/blob/master/inst/segmentation.R). 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: wzxhzdk:5

If one wishes to create a WM mask, could do the following: wzxhzdk:6 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")` |

Jfortin1/MNITemplate documentation built on May 22, 2020, 3:21 a.m.