A hand-eye calibration method for augmented reality applied to computer-assisted orthopedic surgery

2018 ◽  
Vol 15 (2) ◽  
pp. e1969 ◽  
Author(s):  
Marcelo E. de Oliveira ◽  
Henrique G. Debarba ◽  
Alexandre Lädermann ◽  
Sylvain Chagué ◽  
Caecilia Charbonnier
Keyword(s):  
Augmented Reality ◽  
Orthopedic Surgery ◽  
Calibration Method ◽  
Computer Assisted ◽  
Computer Assisted Orthopedic Surgery

A hand-eye calibration method for augmented reality applied to computer-assisted orthopedic surgery

2018 ◽  
Vol 104 (8) ◽  
pp. S110
Author(s):  
Marcelo de Oliveira ◽  
Alexandre Lädermann ◽  
Henrique Debarba ◽  
Sylvain Chagué ◽  
Philippe Collin ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Orthopedic Surgery ◽  
Calibration Method ◽  
Computer Assisted ◽  
Computer Assisted Orthopedic Surgery

scholarly journals An optimized Least-Moving-Point algorithm to detect the hip center

10.29007/clwq ◽  
2018 ◽  
Author(s):  
Guillaume Dardenne ◽  
Zoheir Dib ◽  
Chafiaa Hamitouche ◽  
Christian Lefèvre ◽  
Eric Stindel
Keyword(s):  
Orthopedic Surgery ◽  
Computer Assisted ◽  
Center Of Rotation ◽  
Software Application ◽  
Computer Assisted Orthopedic Surgery

Functional approaches for the localization of the hip center (HC) are widely used in Computer Assisted Orthopedic Surgery (CAOS). These methods aim to compute the HC defined as the center of rotation (CoR) of the femur with respect to the pelvis. The Least-Moving-Point (LMP) method is one approach which consists in detecting the point that moves the least during the circumduction motion. The goal of this paper is to highlight the limits of the native LMP (nLMP) and to propose a modified version (mLMP). A software application has been developed allowing the simulation of a circumduction motion of a hip in order to generate the required data for the computation of the HC. Two tests have been defined in order to assess and compare both LMP methods with respect to (1) the camera noise (CN) and (2) the acetabular noise (AN). The mLMP and nLMP error is respectively: (1) 0.5±0.2mm and 9.3±1.4mm for a low CN, 21.7±3.6mm and 184.7±13.1mm for a high CN, and (2) 2.2±1.2mm and 0.5±0.3mm for a low AN, 35.2±18.5mm and 13.0±8.2mm for a high AN. In conclusion, mLMP is more robust and accurate than the nLMP algorithm.

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