Guoyan Zheng, University of Bern, Stauffacherstrasse 78, CH-3014 Bern, Switzerland
Xuan Zhang, University of Bern, Stauffacherstrasse 78, CH-3014 Bern, Switzerland
Similarity measure is one of the main factors that affect the accuracy of intensity-based 2D-3D registration of X-ray fluoroscopy to CT images. This paper presents a unifying MAP-MFR framework for rationally deriving point similarity measures based on Bayes theorem. Three new similarity measures derived from this framework are presented and evaluated using a phantom and a human cadaveric specimen. Their behaviors are compared to other well-known similarity measures and the comparison results are reported. Combining any one of the new similarity measures with a previously introduced spline-based multiresolution 2D-3D registration scheme, we develop a fast and accurate registration algorithm. We report their capture ranges, converging speeds, and registration accuracies.
Citation:
Guoyan Zheng, Xuan Zhang, "A Unifying MAP-MRF Framework for Deriving New Point Similarity Measures for Intensity-based 2D-3D Registration," icpr, vol. 2, pp.1181-1185, 18th International Conference on Pattern Recognition (ICPR'06) Volume 2, 2006
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