A priori knowledge based particle filter for estimating 3-D pose position of implanted knee
DOI: 10.1109/FUZZY.2010.5584842 Conference: FUZZ-IEEE 2010, IEEE International Conference on Fuzzy Systems, Barcelona, Spain, 18-23 July, 2010, Proceedings
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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