2018
DOI: 10.1002/rcs.1946
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A tensor-mass method-based vascular model and its performance evaluation for interventional surgery virtual reality simulator

Abstract: The vascular model presented herein provides a fundamental module meeting the real-time and realistic requirements of our endovascular interventional surgery simulator.

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Cited by 28 publications
(2 citation statements)
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“…The biomechanical physical behavior of the tissues was implemented using the SOFA simulation toolkit for medical applications, 29 which possess GPU real-time parallel implementations of mass spring, 30 tensor-mass, 31 and finite elements methods (FEMs) 32 . The simulation was implemented as a multimodel representation composed of 4 domains running concurrently: the biomechanical behavior, geometric, visual, and haptic spaces, all synchronized through mapping operations during a simulation loop (Fig.…”
Section: Methodsmentioning
confidence: 99%
“…The biomechanical physical behavior of the tissues was implemented using the SOFA simulation toolkit for medical applications, 29 which possess GPU real-time parallel implementations of mass spring, 30 tensor-mass, 31 and finite elements methods (FEMs) 32 . The simulation was implemented as a multimodel representation composed of 4 domains running concurrently: the biomechanical behavior, geometric, visual, and haptic spaces, all synchronized through mapping operations during a simulation loop (Fig.…”
Section: Methodsmentioning
confidence: 99%
“…Recent advances in VR based training systems assisted by haptic/tactile-feedback, have been treated as promising ways to acquire dexterous catheter manipulation skills. Research towards the development of immersive VR simulators has inspired studies to formulate physical models of both vessels [20], [21] and catheter [22], [23]. With the consideration of tissue-protection, Wang et al made contributions to avoiding possible collisions between catheter tip and vascular wall by both visual and haptic cues [24].…”
Section: Introductionmentioning
confidence: 99%