PublicationDetail

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

D. Zikic, B. Glocker, O. Kutter, M. Groher, N. Komodakis, A. Kamen, N. Paragios, N. Navab
Markov Random Field Optimization for Intensity-based 2D-3D Registration
SPIE Medical Imaging, San Diego, California, USA, 13-18 February 2010 (bib)

We propose a Markov Random Field (MRF) formulation for the intensity-based N-view 2D-3D registration problem. The transformation aligning the 3D volume to the 2D views is estimated by iterative updates obtained by discrete optimization of the MRF model. We employ a pairwise MRF model with a fully connected graph in which the nodes represent the parameter updates and the edges encode the image similarity costs resulting from variations of the values of adjacent nodes. A label space refinement strategy is employed to achieve sub-millimeter accuracy. The evaluation on real and synthetic data and comparison to state-of-the-art method demonstrates 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