AUTHOR=Li Xiaogai , Yuan Qiantailang , Lindgren Natalia , Huang Qi , Fahlstedt Madelen , Östh Jonas , Pipkorn Bengt , Jakobsson Lotta , Kleiven Svein 

TITLE=Personalization of human body models and beyond via image registration

JOURNAL=Frontiers in Bioengineering and Biotechnology

VOLUME=Volume 11 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2023.1169365

DOI=10.3389/fbioe.2023.1169365

ISSN=2296-4185

ABSTRACT=Finite element human body models (HBMs) are becoming increasingly important numerical tools for traffic safety. Developing a validated and reliable HBM from the start requires integrated efforts and continues to be a challenging task. Mesh morphing is an efficient technique to generate personalized HBMs accounting for individual anatomy once a baseline model has been developed. This study presents a new image-registration-based mesh morphing method to generate personalized HBMs. The method is demonstrated by morphing four baseline HBMs (SAFER, THUMS, VIVA+ in both seated and standing posture) into ten subjects with varying heights, body mass indices (BMIs), and sex. The resulting personalized HBMs shows comparable element quality to the baseline models. This method enables the comparison of HBMs by morphing them into the same subject, eliminating geometric differences. The method also shows superior geometry correction capabilities which facilitates converting a seated HBM to a standing posture combined with additional positioning tools. Furthermore, this method can be extended to personalize other models and the feasibility of morphing vehicle models has been illustrated. In conclusion, this new image-registration-based mesh morphing method allows rapid and robust personalization of HBMs, facilitating personalized simulations.