A priori knowledge based particle filter for estimating 3-D pose position of implanted knee.
ABSTRACT For estimating 3-D pose position of artificial knee implants in vivo, there are some studies based on 2-D/3-D image registration of 2-D fluoroscopy images and 3-D geometrical model. Knee implant mainly consists of femoral component and tibial component. Most conventional studies estimate 3-D pose position of femoral component and tibial component individually. Rather, they don't evaluate relative position between the femoral and tibial components. This paper proposes a method for estimating 3-D pose position of implanted knee based on particle filter. A priori knowledge on the relational position of the components are utilized by using fuzzy membership functions. The experimental results for a patient and simulation DR images showed that the proposed method adequately estimate 3-D pose position of the femoral and tibial components with respect to relational position between the components.
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ABSTRACT: A better knowledge of the kinematics behavior of total knee replacement (TKR) during activity still remains a crucial issue to validate innovative prosthesis designs and different surgical strategies. Tools for more accurate measurement of in vivo kinematics of knee prosthesis components are therefore fundamental to improve the clinical outcome of knee replacement. In the present study, a novel model-based method for the estimation of the three-dimensional (3-D) position and orientation (pose) of both the femoral and tibial knee prosthesis components during activity is presented. The knowledge of the 3-D geometry of the components and a single plane projection view in a fluoroscopic image are sufficient to reconstruct the absolute and relative pose of the components in space. The technique is based on the best alignment of the component designs with the corresponding projection on the image plane. The image generation process is modeled and an iterative procedure localizes the spatial pose of the object by minimizing the Euclidean distance of the projection rays from the object surface. Computer simulation and static/dynamic in vitro tests using real knee prosthesis show that the accuracy with which relative orientation and position of the components can be estimated is better than 1.5 degrees and 1.5 mm, respectively. In vivo tests demonstrate that the method is well suited for kinematics analysis on TKR patients and that good quality images can be obtained with a carefully positioning of the fluoroscope and an appropriate dosage. With respect to previously adopted template matching techniques, the present method overcomes the complete segmentation of the components on the projected image and also features the simultaneous evaluation of all the six degrees of freedom (DOF) of the object. The expected small difference between successive poses in in vivo sequences strongly reduces the frequency of false poses and both the operator and computation time.IEEE Transactions on Medical Imaging 11/1999; 18(10):981-91. DOI:10.1109/42.811310 · 3.39 Impact Factor
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ABSTRACT: Two-dimensional (2-D)/three-dimensional (3-D) registration techniques using single-plane fluoroscopy are highly important for analyzing 3-D kinematics in applications such as total knee arthroplasty (TKA) implants. The accuracy of single-plane fluoroscopy-based techniques in the determination of translation perpendicular to the image plane (depth position), however, is relatively poor because a change in the depth position causes only small changes in the 2-D silhouette. Accuracies achieved in depth position using conventional 2-D/3-D registration techniques are insufficient for clinical applications. Therefore, we propose a technique for improving the accuracy of depth position determination in order to develop a system for analyzing knee kinematics over the full six degrees of freedom (6 DOF) using single-plane fluoroscopy. In preliminary experiments, the behaviors of errors for each free variable were quantified as evaluation curves by examining changes in cost function with variations in the free variable. The evaluation curve for depth position was more jagged, and the curve peak less pointy, compared to the evaluation curves of the other five variables, and the curve was found to behave differently. Depth position is therefore optimized independently of the other variables, using an approximate evaluation curve of depth position prepared after initial registration. Accuracy of the proposed technique was evaluated by computer simulation and in vitro tests, with validation of absolute position and orientation performed for each knee component. In computer simulation tests, root-mean-square error (RMSE) in depth position was improved from 2.6 mm (conventional) to 0.9 mm (proposed), whereas for in vitro tests, RMSE improved from 3.2 mm to 1.4 mm. Accuracy of the estimation of the remaining two translational and three rotational variables was found to be almost the same as that obtained by conventional techniques. Results of in vivo tests are also described in which the possibility of full 6 DOF kinematic analysis of TKA implants is shown.IEEE Transactions on Medical Imaging 06/2004; 23(5):602-12. DOI:10.1109/TMI.2004.826051 · 3.39 Impact Factor