Model Construction for the Estimation of Healthy Bone Shape and Density Distribution.

Abstract

Statistical models are widely used within biomedical fields for automated segmentation and reconstruction of healthy geometry. In the absence of contralateral geometry, statistical models are a viable alternative for reconstructing healthy bone anatomy. Therefore, statistical models of shape and appearance were constructed from sample data based on the right femur of South African males, and their use in an automated segmentation and density estimation application was investigated. The models reproduced the shape and density distribution of the population with an average error of 1.3 mm and a 90% density fit. These results fall within the acceptable tolerance limits of reconstructive surgery and appear promising for practical use in implant design.Clinical Relevance- Constructing and validating statistical models and registration algorithms provides the groundwork for further investigation into automating the digital reconstruction of pathological bone for use in implant design.