Modules:AffineRegistration-Documentation-3.4
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Affine Registration
Affine Registration
General Information
Module Type & Category
Type: CLI
Category: Registration
Authors, Collaborators & Contact
- Author: Daniel Blezek
- Contact: daniel.blezek at gmail.com
Module Description
This command line module implements a registration algorithm based on the Mattes mutual information registration metric and the affine transformation. Both the fixed and moving images may be optionally smoothed before registration.
Usage
Examples, Use Cases & Tutorials
- This module is often used to align images of different subjects.
- The affine transformation allows a limited degree of deformation and frequently is used as a pre-processing step for higher order transformations such as the BSpline and Demons.
Quick Tour of Features and Use
List all the panels in your interface, their features, what they mean, and how to use them. For instance:
- Input panel:
- Parameters panel:
- Output panel:
- Viewing panel:
Development
Dependencies
No other modules are required for this module.
Limitations
The module uses an itkOrientImageFilter to realign the fixed and moving images to axial before registration. This is required due to limitations in ITK's handling of non-axial images in filters used by registration.
Known bugs
None. To report 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: C++ Source and XML Description
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 National Centers for Biomedical Computing.
References
D. Mattes, D.R. Haynor, H. Vesselle, T.K. Lewellen, and W. Eubank. PET-CT image registration in the chest using free-form deformations. IEEE Transactions on Medical Imaging, 22(1):120–128, 2003.
