A statistical shape modelling framework and software for predicting skull and muscle networks from head

Real-time biomechanical head simulation is necessary for providing bio-feedbacks for facial paralysis grading. This process is challenging and needs enhancement in both dataset and personalising procedure. We introduced a statistical framework for dataset generation, skull prediction, and muscle strain computation. The head-to-skull shape relation was trained through their shape parameters. After a ten-fold cross-validation, the mean testing error was 1.86 mm with 6.17s ± 0.05s for each fold. The personalised muscle network could be animated by interacting with the system interface for computing the muscle strains. This study has three contributions: a system for personalising and analysing biomechanical head; a procedure for head region cutting and sampling; head-and-skull shapes with their topological features. In perspective, this framework will be used to enhance the accuracy of the head-to-skull prediction. Moreover, we will use the system to generate the standard muscle strains for facial paralysis diagnosing. The dataset is available upon reasonable requests.