Abstract
In virtual vascular interventional surgery, collision detection between surgical instruments and human soft tissue is the basis for deformation and pressure calculation, and it is also a prerequisite for model cutting. Due to the high calculation and complexity in the virtual vascular surgery simulation process, the existing collision detection algorithms can not satisfy the requirements of real-time and accuracy during surgery. Drawing on the deficiencies and improvements of the soft tissue object collision detection algorithm, and combining the unique characteristics of the soft tissue deformation model, a new soft tissue hybrid collision detection algorithm is proposed. Through the two stages of rough detection and precise detection, a large number of redundant calculations in the original collision detection algorithm are omitted, and the response time of collision detection is greatly reduced. Experiments are compared with the other two algorithms to verify that its real-time performance and accuracy have been improved.
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