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PurposeIn this paper, a method for rapidly constructing a virtual surgical simulation system is proposed. A deformation model based on the mechanical properties of the liver and a rapid collision detection between the surgical micro-instruments and the liver tissue are included in this method. The purpose of this work is to improve the accuracy and...
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Context 1
... collision detection between sphere and AABB bounding box is shown in Fig. 8. r is the radius of sphere bounding box, (x min , x max , y min , y max , z min , z max ) is the limit position of AABB bounding box in the direction of three coordinate axes, and (x 0 , y 0 , z 0 ) is the center of sphere bounding box. The two bounding boxes are projected into the plane of three coordinate axes, and the boundary ...
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The application of robotics technology in the medical field can effectively improve the accuracy of surgical operations. However, there is a challenge of movement inconsistency between the end of the laparoscope arm and the surgeon’s hand, as well as the leverage of instruments amplifying the physiological jitter of the surgeon’s hand, which can result in the jitter problem on the slave manipulator and reduce the operating accuracy of the surgical robot. To solve the problem, the Savitzky-Golay filter was used to optimize the trajectory of the master manipulator based on the master-slave mapping method, which was done to eliminate the influence of the physiological jitter. Comparative experiments with other methods were performed to demonstrate the effectiveness of this method. A virtual surgical simulation system and an experimental prototype were proposed to verify the method. The results showed that the method effectively reduced the influence of physiological jitter on master-slave motion control.
Background and objectives:
Virtual reality has been proved indispensable in computer-assisted surgery, especially for surgical planning, and simulation systems. Collision detection is an essential part of surgery simulators and its accuracy and computational efficiency play a decisive role in the fidelity of simulations. Nevertheless, current collision detection methods in surgical simulation and planning struggle to meet precise requirements, especially for detailed and complex physiological structures. To address this, the primary objective of this study was to develop a new algorithm that enables fast and precise collision detection to facilitate the improvement of the realism of virtual reality surgical procedures.
Methods:
The method consists of two main parts, bounding spheres formation and two-level collision detection. A specified surface subdivision method is devised to reduce the radius of basic bounding spheres formed by circumcenters of underlying triangles. The spheres are then clustered and adjusted to obtain a compact personalized hierarchy whose position is updated in real time during surgical simulation, followed by two-level collision detection. Triangular facets with collision potential through interaction between hierarchies and then accurate results are obtained by means of precise detection phase. The effectiveness of the algorithm was evaluated in various models and surgical scenarios and was compared with prior relevant implementations.
Results:
Results on multiple models demonstrated that the method can generate a personalized hierarchy with fewer and smaller bounding spheres for tight wrapping. Simulation experiments proved that the proposed approach is significantly superior to comparable methods under the premise of error-free detection, even for severe model-model collision.
Conclusions:
The algorithm proposed through this study enables higher numerical efficiency and detection accuracy, which is capable of significantly enlarging the fidelity/realism of haptic simulators and surgical planning methods.
