Fascicles Tracking Pipeline

Tracking, reconstruction a analysis of white matter fibers.

Description

Before using this pipeline it is recomended to put your data in a BrainVISA database. See the following process directories for more information :
data management / import / diffusion

There are four subprocesses that can be accessed from this pipeline. They can be used together or individually. Here is a summary of each subprocess purpose :

ROI drawing: With this process you can create or edit a set of region of interest (ROI) with Anatomist 3D ROI drawing tool. This is not really a processing process but it is usefull to have it in the pipeline to benefit from parameters links.

Fiber Tracking: This is the main processing step of fiber analysis : fiber tracking and reconstruction.

Diffusion Bundles Transformation: The Fiber Tracking step produces bundles (i.e. named sets of curves, each curve corresponding to one putative fascicle). It is often necessary to transform bundles into other bundles for example to select only specific fascicles or to apply a referential transformation. This is what this step is for.

Diffusion Bundles Analysis: Once bundles are obtained, they can be visualized in Anatomist but it is also very important to get some quantitative information about the reconstructed fascicle bundles (such as length, fractional anisotropy along the bundle, etc.). This process is dedicated to the extraction of various quantitative information from bundles.

Parameters

t2_diffusion: T2 Diffusion MR ( input )

T2 image extracted from diffusion raw data.

raw_dw_diffusion: Raw DW Diffusion MR ( optional, input )

Diffusion-weighted raw (i.e., non corrected for echoplanar distortions) images.

corrected_dw_diffusion: Corrected DW Diffusion MR ( optional, input )

Diffusion-weighted images corrected for echoplanar distortions.

starting_points: Tracking regions ( optional, input )

Set of region of interest (ROI) used to start fiber tracking. Accepts either a BrainVISA/Anatomist ROI graph (*.arg/*.data file extensions) or an image of labels (each label is considered as a single region).

bundles: Fascicles bundles ( output )

Technical information

Toolbox : Diffusion and Tracking

User level : 0

Identifier : DiffusionTrackingPipeline

File name : /volatile/geffroy/p4/build-stable-Mandriva-2008.0-i686-release/brainvisa/toolboxes/connectomist/processes/DiffusionTrackingPipeline.py

Supported file formats :

t2_diffusion:

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

raw_dw_diffusion:

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

corrected_dw_diffusion:

GIS image

starting_points:

Graph and data, GIS image, SPM image, VIDA image, ECAT v image, ECAT i image, Z compressed GIS image, gz compressed GIS image, Z compressed VIDA image, gz compressed VIDA image, Z compressed SPM image, gz compressed SPM image, Z compressed ECAT v image, gz compressed ECAT v image, Z compressed ECAT i image, gz compressed ECAT i image, JPEG image, GIF image, PNG image, MNG image, BMP image, PBM image, PGM image, PPM image, XBM image, XPM image, TIFF image, TIFF(.tif) image, MINC image, NIFTI-1 image, gz compressed NIFTI-1 image

bundles:

input