Skip to content

dancebean/sammba-mri

 
 

Repository files navigation

https://travis-ci.org/sammba-mri/sammba-mri.svg?branch=master https://coveralls.io/repos/github/sammba-mri/sammba-mri/badge.svg?branch=master https://circleci.com/gh/sammba-mri/sammba-mri.svg?style=svg

sammba-MRI: small mammals neuroimaging with python

Sammba-MRI provides easy-to-use pipelines to process and analyze small mammals brain MRI multimodal images. Sammba-MRI will perform automatically several critical steps for MR image analysis.

  • Conversion of Bruker DICOM files to NIFTI-1
  • Image quality check
  • Image registration and creation of a template
  • Transformation of individual dataset to the template (or to an atlas)
  • Evaluation of cerebral atrophy on the basis of an atlas
  • Estimation of cerebral perfusion maps from FAIR EPI images
  • Resting state fMRI analysis connectivity and brain images visualization are straightforward with nilearn once the registration is performed.

Sammba-MRI integrates functionalities from a number of other packages (listed under the dependencies section below)

Dependencies

The required dependencies to use the software are the software:

  • FSL >= 5.0
  • AFNI
  • ANTs
  • Python >= 3.5
  • RATS for brain extraction

as well as the python packages:

  • setuptools
  • Numpy >= 1.14
  • SciPy >= 0.19
  • Nibabel >= 2.0.2
  • Nilearn >= 0.4.0
  • Sklearn >= 0.19
  • Nipype >= 1.0.4

If you are running the examples, matplotlib >= 1.5.1 is required.

If you want to run the tests, you need nose >= 1.2.1 and doctest-ignore-unicode.

If you want to convert DICOM files to NIFTI files, you will need the DICOM ToolKit (DCMTK) package

User guide and gallery of examples are available on

https://sammba-mri.github.io/

Installation

Sammba-MRI source code can be downloaded with the command:

git clone https://github.com/sammba-mri/sammba-mri

About

small mammals brain MRI

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 99.3%
  • Other 0.7%