@Article{iasc.2021.013541,
AUTHOR = {Xiaorui Zhang, Hailun Wu, Wei Sun, Aiguo Song, Sunil Kumar Jha},
TITLE = {A Fast and Accurate Vascular Tissue Simulation Model Based on Point Primitive Method},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {27},
YEAR = {2021},
NUMBER = {3},
PAGES = {873--889},
URL = {http://www.techscience.com/iasc/v27n3/41651},
ISSN = {2326-005X},
ABSTRACT = {Virtual surgery simulation is indispensable for virtual vascular interventional training system, which provides the doctor with visual scene between catheter and vascular. Soft tissue deformation, as the most significant part, determines the success or failure of the virtual surgery simulation. However, most soft tissue deformation model cannot simultaneously meet the requirement of high deformation accuracy and real-time interaction. To solve the challenge mentioned above, this paper proposes a fast and accurate vascular tissue simulation model based on point primitive method. Firstly, the proposed model simulates a deformation of the internal structure of the vascular tissue by adopting a point primitive method. Besides, the stretching constraint and elastic potential energy constraint are introduced to control and correct node motion. Furthermore, a mapping function from the interior to the surface of the vascular tissue is constructed based on moving least squares algorithm to render the visual effect of deformation. Finally, a training system based on the proposed model is set up on the PHANTOM OMNI force-tactile feedback device to realize the deformation simulation of the virtual vascular tissue. Experimental results shows that the proposed model can enhance real-time performance of the training system under the premise of ensuring deformation accuracy, as well as simulate the elasticity of soft tissue.},
DOI = {10.32604/iasc.2021.013541}
}