Population-specific evaluation of implant bone fitting using PCA shape space and level sets

Currently in orthopedic research, bone shape variability within a specific population has been seldom investigated and used to optimise implant design, which is commonly performed by evaluating implant bone fitting on a limited dataset. In this paper, we extend our method for optimisation in statistical shape space, to global assessment of population-specific implant bone fitting. The method is based on a level set segmentation approach, used on the parametric space of the statistical shape model of the target population. The method highlights which patterns of bone variability are more important for implant fitting, allowing and easing implant design improvements. Results are presented for proximal human tibia.