Modules:ARCTIC-Documentation-3.6

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Gallery of New Features


Module Name

MyModule

ARCTIC logo
T1 skull-stripped image
Parcellation image
Cortical thickness on WM surface
Cortical thickness information

General Information

Module Type & Category

Type: CLI

Category: Pipeline

Authors, Collaborators & Contact

  • Author1: Cedric Mathieu, UNC-Chapel Hill
  • Contributor1: Clement Vachet, UNC-Chapel Hill
  • Contributor2: Martin Styner, UNC-Chapel Hill
  • Contributor3: Heather Cody Hazlett, UNC-Chapel Hill
  • Contact: Clement Vachet, cvachet[at]email[dot]unc[dot]edu

Module Description

ARCTIC (Automatic Regional Cortical ThICkness) is an end-to-end application developped at UNC-Chapel Hill allowing individual analysis of cortical thickness. This cross-platform tool can be run within Slicer3 as an external module, or directly as a command line.

Usage

Use Cases, Examples

This module is especially appropriate when one wants to perform individual regional cortical thickness analysis. ARCTIC allows efficient QC via precomputed 3D-Slicer scenes.

Tutorials

Links to tutorials explaining how to use this module:

  • 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. For instance:

  • Input panel:
    • First input
    • Second input
  • Parameters panel:
    • First parameter
    • Second parameter
  • Output panel:
    • First output
    • Second output
  • Viewing panel:
User Interface

Development

Notes from the Developer(s)

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

Dependencies

None

Tests

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

Known bugs

Links to known bugs in the Slicer3 bug tracker


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:

More Information

Acknowledgment

This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Information on the National Centers for Biomedical Computing can be obtained from http://nihroadmap.nih.gov/bioinformatics

References

Publications related to this module go here. Links to pdfs would be useful.

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