The Gui is very helpful and works really well as a tool for evaluating intensity based image registration. However the core function is a convergence algorithm and possibly because of this, never seems to produce pixel perfect or near perfect registration. It's main advantage is obviously to automate the process without requiring control point user intervention.
Conversely from my experience, imtransform seems to produce better registration results and I can get pixel perfect registration in most cases for my application, but this requires user intervention for control point generation.
What would be really good, from my viewpoint is an algorithm which takes the initial control points from the base image and then automatically searches for equivalent matches in the unregistered image. Any help you can provide in this direction would be a definite five star!
Thank you very much Brett to provide me a comprehensive information. Appreciate your help and looking forward to see more great jobs from you. If I face any issue, i will back to ask you.
Image Registration App is just a front end for the functionality of IMREGISTER.
IMREGISTER is actually a collection of algorithms (optimization + similarity metrics). Because of this, the correct citation would depend on what flavor of optimization and metric you're using.
Here are some applicable references:
Mutual Information based registration:
"Nonrigid multimodality image registration" D. Mattes, D. R. Haynor, H. Vesselle, T. Lewellen and W. Eubank Medical Imaging 2001: Image Processing, 2001, pp. 1609-1620.  "PET-CT Image Registration in the Chest Using Free-form Deformations" D. Mattes, D. R. Haynor, H. Vesselle, T. Lewellen and W. Eubank IEEE Transactions in Medical Imaging. Vol.22, No.1, January 2003. pp.120-128.  "Optimization of Mutual Information for MultiResolution Image Registration" P. Thevenaz and M. Unser IEEE Transactions in Image Processing, 9(12) December 2000.
One Plus One Evolutionary Optimizer:
"Parametric estimate of intensity inhomogeneities applied to MRI" Martin Styner, G. Gerig, Christian Brechbuehler, Gabor Szekely, IEEE TRANSACTIONS ON MEDICAL IMAGING; 19(3), pp. 153-165, 2000, (http://www.cs.unc.edu/~styner/docs/tmi00.pdf)
"Evaluation of 2D/3D bias correction with 1+1ES-optimization" Martin Styner, Prof. Dr. G. Gerig (IKT, BIWI, ETH Zuerich), TR-197 (http://www.cs.unc.edu/~styner/docs/StynerTR97.pdf)
Most of the literature seems to take the basic similarity metric/ optimization framework for granted without citing references. The references are usually for specific parts of the framework (numeric optimization, image similarity metrics, ways of pyramiding, etc.).
Hope that helps,
Hello Mr. Brett Shoelson,
Thank you very much for provide this implementation. i want to use this method as comparison in my journal paper. i need to cite the basic journal paper of this implementation. please provide me the citation if any.
Thank you very much.
I am not sure what you mean by "manual...GUI." But it probably wouldn't make any difference if I did. While IMREGCONFIG, IMREGISTER, and IMREF3D all facilitate 3D image registration, I haven't incorporated that capacity into this application, nor am I aware of any GUI that does. You might find the demo on "Registering Multimodal 3-D Medical Images" useful, though.