NDLI: A Statistical Approach to Determine Symmetrical Solutions for the Registration of 3D Knee Implant Models to Sagittal Fluoroscopy Images

Content Provider	IEEE Xplore Digital Library
Author	Hermans, J. Bellemans, J. Vandermeulen, D. Suetens, P.
Copyright Year	2007
Description	Author affiliation: Katholieke Univ. Leuven, Leuven (Hermans, J.; Bellemans, J.; Vandermeulen, D.; Suetens, P.)
Abstract	During the registration of 3D CAD models of metallic knee implant components to single-plane sagittal fluoroscopy images, the 3D pose of each implant component is estimated by maximizing the similarity between its 2D image appearance and the observed fluoroscopy image. Because knee implant components are highly symmetrical with respect to the sagittal plane, two significantly different model poses result in 2D image projections very similar to an observed sagittal fluoroscopy image. Traditional 2D/3D registration algorithms tend to converge to one of these symmetrical poses discarding the other one. This paper presents a method which simultaneously estimates both symmetrical solutions. In order not to limit the proposed method to 3D models with an exact plane of symmetry, a completely data-driven symmetry constraint is used which is imposed to the estimated pose parameters. The algorithm is embedded in a statistical framework which is optimized using a deterministic annealing expectation-maximization approach. The validity of the method is demonstrated by registration of the tibial knee implant component to real and simulated fluoroscopy images.
Starting Page	1
Ending Page	8
File Size	845694
Page Count	8
File Format	PDF
ISBN	9781424416301
ISSN	15505499
DOI	10.1109/ICCV.2007.4409158
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-14
Publisher Place	Brazil
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Knee Implants Video sequences Image converters Kinematics Image edge detection Annealing Convergence Biomedical imaging Hospitals
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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