Shape Morphing Technique Can Accurately Predict Pelvic Bone Landmarks

Abstract

AbstractDiffeomorphic shape registration allows for the seamless geometric alignment of shapes. In this study, we demonstrated the use of a registration algorithm to automatically seed anthropological landmarks on the CT images of the pelvis. We found a high correlation between manually and automatically seeded landmarks. The registration algorithm makes it possible to achieve a high degree of automation with the potential to reduce operator errors in the seeding of anthropological landmarks. The results of this study represent a promising step forward in effectively defining the anthropological measures of the human skeleton.HighlightsThe clinical CT scan is a feasible alternative to skeletal collections and body donor programs.Pelvic morphology is complex, sexually dimorphic and is proven to being a good demonstration model for the performance analysis of registration algorithm for automatic landmark seeding.The landmark seeding using registration algorithm can save time and effort in anthropological analysis.