DocumentCode :
687439
Title :
On A Priori Knowledge in Particle Filter for In-Vivo Analysis of Implanted Knee
Author :
Tada, Shigeru ; Kobashi, Shoji ; Kuramoto, Koji ; Imamura, Fumiaki ; Morooka, Takatoshi ; Yoshiya, Shinich ; Hata, Yuki
Author_Institution :
Grad. Sch. of Eng., Univ. of Hyogo, Himeji, Japan
fYear :
2013
fDate :
10-12 Dec. 2013
Firstpage :
168
Lastpage :
171
Abstract :
Total knee arthroplasty (TKA) is an orthopedic surgery which replaces the damaged knee joint with the artificial one. To diagnose the function of the implanted knee joint, it is effective to estimate 3-D knee kinematics in vivo. There are some conventional methods for estimating kinematics of the implanted knee using 2-D/3-D image registration for X-ray fluoroscopic images and 3-D geometrical models of the knee implant. This paper proposes a method for analyzing knee kinematics based on particle filter which became high precision using priori knowledge. The experimental results showed that the proposed method left the grade that was better than non-priori-knowledge method.
Keywords :
diagnostic radiography; image registration; medical image processing; particle filtering (numerical methods); prosthetics; surgery; 3D geometrical models; 3D knee kinematics estimation; TKA; X-ray fluoroscopic images; a priori knowledge; image registration; implanted knee; in-vivo analysis; orthopedic surgery; particle filter; total knee arthroplasty; Bones; Estimation; Implants; Joints; Kinematics; Particle filters; X-ray imaging; 2-D/3-D Image Registration; Particle Filter; Priori Knowledge; Total Knee Arthroplasty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robot, Vision and Signal Processing (RVSP), 2013 Second International Conference on
Conference_Location :
Kitakyushu
Print_ISBN :
978-1-4799-3183-5
Type :
conf
DOI :
10.1109/RVSP.2013.46
Filename :
6830006
Link To Document :
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