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Gallery of New Features

ACPC Transform

ACPC Transform

After calculating the transform

General Information

Module Type & Category

Type: CLI

Category: Registration

Authors, Collaborators & Contact

  • Nicole Aucoin: Brigham and Women's Hospital
  • Contact: Nicole Aucoin,

Module Description

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.


Examples, Use Cases & Tutorials

  • Useful when can place fiducials in two orthogonal lines in a an image to define the midline and the ACPC line

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.



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 calcualted.

Known bugs

Follow this link to 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

Source Code:

Doxygen documentation:

More Information


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.