Skip to content
lipsia3.0
C C++ Other
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
bin
docs added vapplymask, vbinarize Oct 18, 2019
include
lib
src
.gitignore new ECM Dec 13, 2018
Dockerfile
INSTALL.rst Makefile vpreprocess changed Jun 5, 2019
LICENSE.md update Oct 2, 2017
README.rst 3.1.0 release May 13, 2019
lipsia-setup.sh minro change in lipsia_setup Jun 5, 2019

README.rst

LIPSIA 3.1.0 (May 13, 2019): fMRI analysis tools

Lipsia is a collection of tools for the analysis of fMRI data. Its main focus is on new algorithms such as statistical inference (LISA), Eigenvector centrality mapping (ECM) and network detection in task-fMRI (TED). Below, a brief description follows. For further details see documentation.

Installation

Lipsia currently supports Linux and all other operating systems via Docker. Follow the instructions here: install.

Documentation

Find the full lipsia documentation here: documentation.

Statistical inference (LISA) in examples:

Onesample test at the 2nd level (vlisa_onesample). Example: the input is a set of contrast maps called "data_*.nii.gz":

vlisa_onesample -in data_*.nii.gz -mask mask.nii -out result.v
vnifti -in result.v -out result.nii

Twosample test at the 2nd level (vlisa_twosample). Example: input are two sets of contrast maps called "data1_*.nii.gz" and "data2_*.nii.gz":

vlisa_twosample -in1 data1_*.nii.gz -in2 data2_*.nii.gz -mask mask.nii -out result.v
vnifti -in result.v -out result.nii

Single subject test (1st level) (vlisa_prewhitening). Example: input are two runs acquired in the same session called "run1.nii.gz" and "run2.nii.gz". Preprocessing should include a correction for baseline drifts!:

vlisa_prewhitening -in run1.nii.gz run2.nii.gz -design des1.txt des2.txt -mask mask.nii -out result.v
vnifti -in result.v -out result.nii

Eigenvector centrality mapping (ECM) in examples:

Example: input is an fMRI data set called "data.nii.gz" and a brain mask called "mask.nii.gz".:

vecm -in data.nii.gz -mask mask.nii.gz -j 0 -out ecm.v
vnifti -in ecm.v -out ecm.nii

Lipsia file format

Lipsia uses its own data format, which is called vista (extension .v). Many lipsia programs also accept gzipped files or nifti-files as input (.v.gz or .nii.gz). The output is always in unzipped vista-format. You can easily convert your nifti data from and to lipsia with the program *vnifti:

vnifti -in data.nii -out data.v
vnifti -in data.nii.gz -out data.v
vnifti -in result.v -out result.nii

Alternatively, you can import a folder with DICOM files into the vista format:

vdicom -in dir_dicom

Preprocessing

The current release contains only a rudimentary set of preprocessing tools. Preprocessing should therefore be performed beforehand using other software packages. Note that some lipsia algorithms require that the preprocessing pipeline contains a removal of baseline drifts. This step can be done using the lipsia program "vpreprocess" if it was omitted in the initial preprocessing.

You can’t perform that action at this time.