Module Type & Category
Authors, Collaborators & Contact
- Nicole Aucoin: Brigham and Women's Hospital
- Contact: Nicole Aucoin, email@example.com
Calculate a transformation from two input fiducial lists.
This transformation can then be applied to a volume using the Resample Scalar/Vector/DWI Volume module.
Note: renamed from RealignVolume.
Use Cases, Examples
This module is especially appropriate for these use cases:
- Use Case 1: place fiducials in two orthogonal lines in a an image to define the midline and the ACPC line
- Use Case 2:
Examples of the module in use:
- Example 1
- Example 2
Links to tutorials explaining how to use this module:
- Tutorial 1
- Data Set 1
Quick Tour of Features and Use
- Transform panel: Calculate a transform from midline and ACPC fiducial lists, and specify an output transform.
- ACPC Line: a fidicual list containing two fiducial points, one at the anterior commissure and one at the posterior commissure. The resulting transform will bring the line connecting them to horizontal to the AP axis.
- Midline: pick a fiducial list from the scene that defines the midline. The midline is a series of points defining the division between the left and right hemispheres of the brain (the mid sagittal plane). The resulting transform will put the output volume with the mid sagittal plane lined up with the AS plane.
- Output transform: An output transform - load the calculated transform in this node.
- Debug panel: Set debugging flag
- Debug: click to see print outs
- Use: the order in which the acpc fiducials are picked is not important.
Notes from the Developer(s)
Ported from Slicer 2.6.
The fiducials module is required for this module's use. The Resample Scalar/Vector/DWI Volume module can be used to apply the transform once it has been calculated.
On the Dashboard, these tests verify that the module is working on various platforms:
- ACPCTest ACPCTest.cxx
Follow this link to the Slicer3 bug tracker.
Follow this link to the Slicer3 bug tracker. Please select the usability issue category when browsing or contributing.
Source code & documentation
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.