Tetrahedral framework registration algorithm for the robot-assisted surgical navigation system

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.

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