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