Generic Diffusion Importation

A generic process to import diffusion data from various scanners.

Description

This process can be used to import most image acquired on various scanners. File organization varies according to the scanners, and there is no standard way for storing diffusion acquisiton data such as b-values and gradient orientation. Therefore, the input of this process is composed of a set of 3D or 4D images containing acquired data and a text file which contains the bvalues and gradient orientation information.

How to write the bValuesAndOrientations file ?

This text file is used to associate one b-value and one diffusion gradient orientation for each 3D volume contained in the series of input images. The series of input images is considered as a vector of 3D volumes by concatenating images. Each line of bValuesAndOrientations file is associated to one 3D volume in the vector. The text file must have as many lines as there are 3D volumes in input images. Each line is composed of four numbers. The first one is a b-value and the three other ones represent a diffusion gradient orientation.

Example

Suppose that you have acquired data with 6 gradient directions and two b-values. The data are in two files. The first file is a 4D image containing one T2 image followed by 6 diffusion-weighted (one per direction) images for b-value=1500. The second file is a 4D image containing another T2 image followed by 6 diffusion-weighted images acquired with b-value=3000. The bValuesAndOrientations file would have the following content:

0 0 0 0
1500 0 0 1
1500 0 1 0
1500 0 1 1
1500 1 0 0
1500 1 0 1
1500 1 1 1
0 0 0 0
3000 0 0 1
3000 0 1 0
3000 0 1 1
3000 1 0 0
3000 1 0 1
3000 1 1 1

Parameters

files: ListOf ( input )

Input data files containing both T2 and diffusion weighted data.

bValuesAndOrientations: Text file ( input )

Text file which indicates b-values and gradient orientations.

t2_diffusion: Raw T2 Diffusion MR ( output )

Output file name for the mean T2 image.

dw_diffusion: Raw DW Diffusion MR ( output )

Output file name for the diffusion weighted data.

dw_already_corrected: Boolean ( input )

Indicate if diffusion-weighted is already corrected for echoplanar distorsion correction. If images are already corrected, the correction process will be unselected by default in the pipeline.

Technical information

Toolbox : Diffusion and Tracking

User level : 0

Identifier : DiffusionGenericImport

File name : brainvisa/toolboxes/connectomist/processes/Import/DiffusionGenericImport.py

Supported file formats :

bValuesAndOrientations :

Text file

t2_diffusion :

GIS image, VIDA image, NIFTI-1 image, MINC image, TIFF image, XBM image, PBM image, PGM image, BMP image, XPM image, PPM image, gz compressed NIFTI-1 image, ECAT i image, PNG image, JPEG image, MNG image, GIF image, SPM image, ECAT v image

dw_diffusion :

GIS image, VIDA image, NIFTI-1 image, MINC image, TIFF image, XBM image, PBM image, PGM image, BMP image, XPM image, PPM image, gz compressed NIFTI-1 image, ECAT i image, PNG image, JPEG image, MNG image, GIF image, SPM image, ECAT v image