Visual Modelling and Rendering for Virtual Reality Based Surgical Simulation

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The lack of effective methods and tools for surgical training has been a long-standing problem in medical education. Current approaches exhibit various limitations and drawbacks: animals have different anatomies from humans; cadavers are unable to provide physiological responses; it is risky for surgical residents to practice on patients. A recent CBC report shows that a great percentage of Canadian surgical residents do not demonstrate basic hands-on skills and manual dexterity.     Because of its many unique advantages, virtual-reality based surgical simulators are increasingly regarded as a promising solution to the current predicament, representing next-generation paradigm for surgical training. A surgical simulator is able to generate virtual patients with human anatomy and physiological responses, providing a risk-free training environment. In addition to these obvious benefits, surgery residents can practice on a wide range of pathological states with unlimited times; new complex surgical procedures can be tried safely on a surgical simulator before proceeding to patients.     Current surgical simulators, however, are still in their infancy and there exist numerous technical challenges and difficulties. In particular, no simulator is able to provide a sufficiently high degree of visual resemblance to real-life surgery. Aiming at solving this problem, this proposal will deal with some key issues about the visual feedback of surgical simulation: physical modelling (i.e., the modelling of soft tissue's biomechanical properties), geometric modelling (the modelling of soft tissue's deformation) and visual rendering. The anticipated results will be implemented and validated in the development of a neurosurgery simulator prototype.     The long-term goal is to develop principles, algorithms and tools that are essential to realize highly realistic and naturalistic visual feedback for surgical simulation, enabling educational institutions and hospitals to train surgeons (particularly neurosurgeons) using virtual-reality based simulators. To achieve this goal, specific research objectives are as follows:     - To develop suitable models to incorporate anisotropic, viscoelastic and physiological features, improving the modelling accuracy of the physical (biomechanical) properties of human soft tissue;     - To explore to extract the biomechanical parameters of human soft tissue using CT and/or MRI images, addressing the dilemma due to various difficulties associated with current methods;     - To develop a meshless approach to geometric models for the deformation of human soft tissue;     - To develop rendering methods to mix/integrate seamlessly simulated surgical scenes with real surgical video as the background, achieving high degree of visual immersion;      - To apply anticipated results to develop a new neurosurgery simulator in collaboration with the industrial partner and clinical practitioner.