Master of Engineering Science
Surgical simulators are technological platforms that provide virtual substitutes to the current cadaver-based medical training models. The advantages of exposure to these devices have been thoroughly studied, with enhanced surgical proficiency being one of the assets gained after extensive use. While simulators have already penetrated numerous medical domains, the field of orthopedics remains stagnant despite a demand for the ability to practice uncommon surgeries, such as total shoulder arthroplasty (TSA). Here we extrapolate the algorithms of an inhouse software engine revolving around glenoid reaming, a critical step of TSA. The project’s purpose is to provide efficient techniques for future simulators, and the methods developed address the challenges of achieving real-time performance with high-volume computations and haptics input rates. The core of the engine revolves around the management and manipulation of voxels, which handle the representation of virtual objects, the collision between them, and the removal of material upon interaction. A partitioning (“Chunk”) system was implemented for performant voxel organization and collision handling. Compared to object-wide single voxel buffers or 3D textures, chunks enable empty-space memory savings and optimized collision testing through region isolation. Overall, the engine can replicate the interaction between a ~30 million voxel scapula and a drill at 60 Hz visual, 1 kHz haptics, and 333 Hz collisions. We anticipate that the techniques developed will further the development of current and future simulators.
Popa, Vlad, "Haptics-enabled, GPU augmented surgical simulation platform for glenoid reaming" (2019). Electronic Thesis and Dissertation Repository. 6143.
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