Combined registration of 3D tibia and femur implant models in 3D magnetic resonance images

Karl-Hans Englmeier; Markus Siebert; Ruediger von Eisenhart-Rothe; Heiko Graichen

doi:10.1117/12.769439

12 March 2008 Combined registration of 3D tibia and femur implant models in 3D magnetic resonance images

Karl-Hans Englmeier, Markus Siebert, Ruediger von Eisenhart-Rothe, Heiko Graichen

Proceedings Volume 6916, Medical Imaging 2008: Physiology, Function, and Structure from Medical Images; 691620 (2008) https://doi.org/10.1117/12.769439
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

The most frequent reasons for revision of total knee arthroplasty are loosening and abnormal axial alignment leading to an unphysiological kinematic of the knee implant. To get an idea about the postoperative kinematic of the implant, it is essential to determine the position and orientation of the tibial and femoral prosthesis. Therefore we developed a registration method for fitting 3D CAD-models of knee joint prostheses into an 3D MR image. This rigid registration is the basis for a quantitative analysis of the kinematics of knee implants. Firstly the surface data of the prostheses models are converted into a voxel representation; a recursive algorithm determines all boundary voxels of the original triangular surface data. Secondly an initial preconfiguration of the implants by the user is still necessary for the following step: The user has to perform a rough preconfiguration of both remaining prostheses models, so that the fine matching process gets a reasonable starting point. After that an automated gradient-based fine matching process determines the best absolute position and orientation: This iterative process changes all 6 parameters (3 rotational- and 3 translational parameters) of a model by a minimal amount until a maximum value of the matching function is reached. To examine the spread of the final solutions of the registration, the interobserver variability was measured in a group of testers. This variability, calculated by the relative standard deviation, improved from about 50% (pure manual registration) to 0.5% (rough manual preconfiguration and subsequent fine registration with the automatic fine matching process).

Citation Download Citation

Karl-Hans Englmeier, Markus Siebert, Ruediger von Eisenhart-Rothe, and Heiko Graichen "Combined registration of 3D tibia and femur implant models in 3D magnetic resonance images", Proc. SPIE 6916, Medical Imaging 2008: Physiology, Function, and Structure from Medical Images, 691620 (12 March 2008); https://doi.org/10.1117/12.769439

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KEYWORDS

Image registration

3D modeling

3D image processing

Magnetic resonance imaging

Data modeling

Kinematics

Data conversion

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