TY - GEN
T1 - Tetrahedral framework registration algorithm for the robot-Assisted surgical navigation system
AU - Zhu, Jiebao
AU - Sun, Yu
AU - Gao, Peng
AU - Ma, Kailin
AU - Hu, Ying
AU - Cao, Yong
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/24
Y1 - 2017/1/24
N2 - The accuracy of registration is one of the key issues in surgical navigation, which directly affects the result of operation. In this paper, we proposed a new registration algorithm, Tetrahedral Framework (TF), to improve precision and computing speed and conducted a calibration experiment by using the wax model with markers. The image data are obtained by Micro-CT scanning and loaded in VTK to gain the coordinate of the markers, while the tracking data in real space are collected from NDI equipment. The proposed TF algorithm can be described as follow. Firstly, the two point-sets are respectively divided into a tetrahedral framework part and a few of particles; secondly, the scale coefficient is calculated for mapping the image data into the real space; finally, the particle swarm optimization (PSO) is used to adjust the positions and attitude of image framework to acquire a maximal projection on the tracking framework planes. In order to improve the precision of registration, we combined the particles information in an optimization process. Besides, the experimental results show that the algorithm can satisfy the requirement in surgical navigation.
AB - The accuracy of registration is one of the key issues in surgical navigation, which directly affects the result of operation. In this paper, we proposed a new registration algorithm, Tetrahedral Framework (TF), to improve precision and computing speed and conducted a calibration experiment by using the wax model with markers. The image data are obtained by Micro-CT scanning and loaded in VTK to gain the coordinate of the markers, while the tracking data in real space are collected from NDI equipment. The proposed TF algorithm can be described as follow. Firstly, the two point-sets are respectively divided into a tetrahedral framework part and a few of particles; secondly, the scale coefficient is calculated for mapping the image data into the real space; finally, the particle swarm optimization (PSO) is used to adjust the positions and attitude of image framework to acquire a maximal projection on the tracking framework planes. In order to improve the precision of registration, we combined the particles information in an optimization process. Besides, the experimental results show that the algorithm can satisfy the requirement in surgical navigation.
KW - Error analysis
KW - Image navigation
KW - Registration algorithm
KW - Surgical robot
KW - Tetrahedral framework
UR - https://www.scopus.com/pages/publications/85015764419
U2 - 10.1109/ICInfA.2016.7831915
DO - 10.1109/ICInfA.2016.7831915
M3 - 会议稿件
AN - SCOPUS:85015764419
T3 - 2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016
SP - 726
EP - 731
BT - 2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016
Y2 - 1 August 2016 through 3 August 2016
ER -