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Anchorage, AK, USA
June 23, 2008 to June 28, 2008
ISBN: 978-1-4244-2339-2
pp: 1-8
J. Bellemans , Faculties of Engineering and Medicine, Katholieke Universiteit Leuven, University Hospital Gasthuisberg, Herestraat 49, B-3000, Belgium
F. Maes , Faculties of Engineering and Medicine, Katholieke Universiteit Leuven, University Hospital Gasthuisberg, Herestraat 49, B-3000, Belgium
D. Vandermeulen , Faculties of Engineering and Medicine, Katholieke Universiteit Leuven, University Hospital Gasthuisberg, Herestraat 49, B-3000, Belgium
P. Suetens , Faculties of Engineering and Medicine, Katholieke Universiteit Leuven, University Hospital Gasthuisberg, Herestraat 49, B-3000, Belgium
ABSTRACT
Registration of 3D knee implant components to single-plane X-ray image sequences provides insight into implanted knee kinematics. In this paper a Maximum Likelihood approach is proposed to align the pose-related occluding contour of an object with edge segments extracted from a single-plane X-ray image. This leads to an Expectation Maximization algorithm which simultaneously determines the object’s pose, estimates point correspondences and rejects outlier points from the registration process. Considering (nearly) planar-symmetrical objects, the method is extended in order to simultaneously estimate two symmetrical object poses which both align the corresponding occluding contours with 2D edge information. The algorithm’s capacity to generate accurate pose estimates and the necessity of determining both symmetrical poses when aligning (nearly) planar-symmetrical objects will be demonstrated in the context of automated registration of knee implant components to simulated and real single-plane X-ray images.
CITATION
J. Bellemans, F. Maes, D. Vandermeulen, P. Suetens, "A statistical framework for the registration of 3D knee implant components to single-plane X-ray images", CVPRW, 2008, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops 2008, pp. 1-8, doi:10.1109/CVPRW.2008.4563004
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