12 March 2010 Markov random field optimization for intensity-based 2D-3D registration
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Abstract
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 proposed 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.
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Darko Zikic, Darko Zikic, Ben Glocker, Ben Glocker, Oliver Kutter, Oliver Kutter, Martin Groher, Martin Groher, Nikos Komodakis, Nikos Komodakis, Ali Khamene, Ali Khamene, Nikos Paragios, Nikos Paragios, Nassir Navab, Nassir Navab, } "Markov random field optimization for intensity-based 2D-3D registration", Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 762334 (12 March 2010); doi: 10.1117/12.837232; https://doi.org/10.1117/12.837232
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