Symmetric normalization algorithm for estimating physiological strain in bones

Abstract

This study evaluates the accuracy of the Symmetric Normalization (SyN) algorithm in estimating physiological bone deformations using digital volume correlation (DVC), comparing it to the well-established BoneDVC algorithm commonly employed in bone biomechanics. Using high-resolution micro-CT images of the proximal femur and synthetic deformation models, we assessed the precision and robustness of each algorithm. Findings indicate that SyN produces comparable error levels to BoneDVC, with reduced sensitivity to noise and sampling rates. In contrast, BoneDVC’s accuracy is more dependent on nodal spacing configuration, which impacts deformation estimates. These results suggest that SyN, with its efficient noise handling and computational advantages, may serve as a viable alternative for bone deformation analysis in DVC experiments. This study contributes novel insights into the application of SyN-based algorithms in biomechanical research, offering a foundation for future investigations across diverse bone structures and experimental settings.