dtiprocess:Fibertrack

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fibertrack

General Information

Module Type & Category

Type: CLI

Category: DTI.DTIProcess

Authors, Collaborators & Contact

Author: Casey Goodlett

Contributors: Hans Johnson, Sylvain Gouttard

Contact: Sylvain Gouttard, gouttard@sci.utah.edu

Module Description

Program title	fibertrack
Program description	This program implements a simple streamline tractography method based on the principal eigenvector of the tensor field. A fourth order Runge-Kutta integration rule used to advance the streamlines. As a first parameter you have to input the tensor field (with the --input_tensor_file option). Then the region of interest image file is set with the --input_roi_file. Nextyou want to set the output fiber file name after the --output_fiber_file option. You can specify the label value in the input_roi_file with the --target_label, --source_label and --fobidden_label options. By default target label is 1, source label is 2 and forbidden label is 0. The source label is where the streamlines are seeded, the target label defines the voxels through which the fibers must pass by to be kept in the final fiber file and the forbidden label defines the voxels where the streamlines are stopped if they pass through it. There is also a --whole_brain option which, if enabled, consider both target and source labels of the roi image as target labels and all the voxels of the image are considered as sources. During the tractography, the --fa_min parameter is used as the minimum value needed at different voxel for the tracking to keep going along a streamline. The --step_size parameter is used for each iteration of the tracking algorithm and defines the length of each step. The --max_angle option defines the maximum angle allowed between two successive segments along the tracked fiber.
Program version	1.1.0
Program documentation-url	http://www.google.com/

Usage

Use Cases, Examples

This module is especially appropriate for these use cases:

Use Case 1:
Use Case 2:

Examples of the module in use:

Example 1:
Example 2:

Tutorials

Tutorial 1
- Data Set 1

Quick Tour of Features and Use

A list panels in the interface, their features, what they mean, and how to use them.

Input Tensor File
- Input Tensor File [----input_tensor_file] [-i]: Tensor Image
- Input Tensor File [----input_roi_file] [-r]: The filename of the image which contains the labels used for seeding and constraining the algorithm.
- Output Fiber File [----output_fiber_file] [-o]: The filename for the fiber file produced by the algorithm. This file must end in a .fib or .vtk extension for ITK spatial object and vtkPolyData formats respectively.
- If this option is enabled all voxels in the image are used to seed tractography. When this option is enabled both source and target labels function as target labels [----whole_brain] : Default value: false
- Verbose [----verbose] [-v]: produce verbose output Default value: 0
- Really Verbose [----really_verbose] : Follow detail of fiber tracking algorithm Default value: 0
- Force [----force] : Ignore sanity checks. Default value: 0

Image:ScreenshotBlankNotOptional.png

User Interface

Development

Notes from the Developer(s)

Algorithms used, library classes depended upon, use cases, etc.

Dependencies

Other modules or packages that are required for this module's use.

Tests

On the Dashboard, these tests verify that the module is working on various platforms:

MyModuleTest1 MyModuleTest1.cxx
MyModuleTest2 MyModuleTest2.cxx

Known bugs

Links to known bugs in the Slicer3 bug tracker

Bug 000: description

Usability issues

Follow this link to the Slicer3 bug tracker. Please select the usability issue category when browsing or contributing.

Source code & documentation

Links to the module's source code:

Source code:

Doxygen documentation:

class1

More Information

Acknowledgment

Hans Johnson(1,3,4); Kent Williams(1); (1=University of Iowa Department of Psychiatry, 3=University of Iowa Department of Biomedical Engineering, 4=University of Iowa Department of Electrical and Computer Engineering) provided conversions to make DTIProcess compatible with Slicer execution, and simplified the stand-alone build requirements by removing the dependancies on boost and a fortran compiler.