GRIDiron: An Interactive Authoring and Cognitive Training Foundation for Reconstructive Plastic Surgery Procedures

Nathan M. Mitchell University of Wisconsin, Madison
Court Cutting New York University
Eftychios Sifakis University of Wisconsin, Madison

We present an interactive simulation framework for authoring surgical procedures of soft tissue manipulation using physics-based simulation to animate the flesh. This interactive authoring tool can be used by clinical educators to craft three-dimensional illustrations of the intricate maneuvers involved in craniofacial repairs, in contrast to two-dimensional sketches and still photographs which are the medium used to describe these procedures in the traditional surgical curriculum. Our virtual environment also allows surgeons-intraining to develop cognitive skills for craniofacial surgery by experimenting with different approaches to reconstructive challenges, adapting stock techniques to flesh regions with nonstandard shape, and reach preliminary predictions about the feasibility of a given repair plan. We use a Cartesian grid-based embedded discretization of nonlinear elasticity to maximize regularity, and expose opportunities for aggressive multithreading and SIMD accelerations. Using a grid-based approach facilitates performance and scalability, but constrains our ability to capture the topology of thin surgical incisions. We circumvent this restriction by hybridizing the grid-based discretization with an explicit hexahedral mesh representation in regions where the embedding mesh necessitates overlap or nonmanifold connectivity. Finally, we detail how the front-end of our system can run on lightweight clients, while the core simulation capability can be hosted on a dedicated server and delivered as a network service.

SIMD (Single Instruction Multiple Data) numerical kernels used for accelerating finite element computations on hardware with vector instruction sets (SSE, AVX, MIC).
N. Mitchell, C. Cutting, and E. Sifakis GRIDiron: An interactive authoring and cognitive training foundation for reconstructive plastic surgery procedures in proceedings of ACM SIGGRAPH, 2015