Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

THIS WEBPAGE IS DEPRECATED - please visit our new website

B. Glocker, D. Zikic, N. Komodakis, N. Paragios, N. Navab
Linear Image Registration through MRF Optimization
IEEE International Symposium on Biomedical Imaging (ISBI), Boston, MA, USA, June 28-July 1 2009. (bib)

We propose a Markov Random Field formulation for the linear image registration problem. Transformation parameters are represented by nodes in a fully connected graph where the edges model pairwise dependencies. Parameter estimation is then solved through iterative discrete labeling and discrete optimization while a label space refinement strategy is employed to achieve sub-millimeter accuracy. Our framework can encode any similarity measure, allows for automatic reduction of the degrees of freedom by simple changes on the MRF topology, and is robust to initialization. Promising results on real data and random studies demonstrate the potential of our approach.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each authors copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Edit | Attach | Refresh | Diffs | More | Revision r1.13 - 30 Jan 2019 - 15:16 - LeslieCasas

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif