Understanding the mechanics of orthopedic surgery is particularly important for cementless press-fitted implants, which introduce additional strains in the bone at the time of insertion. The innovative aspect of my research is to incorporate biomechanical analysis into pre-operative planning and to apply it to simulation of Total Hip Replacement surgery. No robust automatic general algorithms exist for these tasks. The new approach I am pursuing is to couple these two tasks and to apply deformable mapping algorithms for obtaining the finite element model from CT data. When the mapping is established, the mesh can be readily mapped from the template to the patient-specific model.
Deformable mapping is an area of active research.
Scientists have found it useful to use deformable mappings for brain segmentation of patient-specific MRI data. Imaging algorithms, deformable mapping techniques and complex geometry of anatomical structure place significant requirements on computing resources. By building my code on top of the PETSc parallel numerical library, I can exploit the speed and memory of high-end parallel computers. Available gigaflop computing and fast mapping algorithms will permit construction of patient-specific finite element models in reasonable time.