Title: A statistical shape modelling method for predicting the human head from the face

Authors: Vi-Do Tran; Phong-Phu Vo; Ngoc-Lan-Nhi Tran; Tien-Tuan Dao; Tan-Nhu Nguyen

Addresses: Ho Chi Minh City University of Technology and Education, Vietnam ' Ho Chi Minh City University of Technology and Education, Vietnam ' School of Biomedical Engineering, International University, Zone 6, Linh Trung Ward, Thu Duc City, Ho Chi Minh City, Vietnam; Vietnam National University Ho Chi Minh City, Vietnam ' Univ. Lille, CNRS, Centrale Lille, UMR 9013-LaMcube-Laboratoire de Mécanique, Multiphysique, Multiéchelle, Lille, F-59000, France ' School of Biomedical Engineering, International University, Zone 6, Linh Trung Ward, Thu Duc City, Ho Chi Minh City, Vietnam; Vietnam National University Ho Chi Minh City, Vietnam

Abstract: Predicting the back head based only on the face is necessary for generating the full head and skull. We prepared a dataset of 329 surface meshes of the head. These meshes were reconstructed and post-processed from computed tomography (CT) image sets of adult subjects having normal head structures. A novel back head and face sampling technique was also developed for acquiring back head and face features. The relation between the face features and the back head features was trained using four strategies: non-rigid scaling, SSM optimization, partial least squares regression (PLSR), and principal component analysis (PCA). A ten-fold cross-validation procedure was conducted for selecting the optimal training strategies and tuning their parameters. The face features and the predicted back head features formed the head. The mean mesh-to-mesh distances between the predicted and the ground truth back head were (mean ± SD) 1.15 ± 0.21 mm. The method will enhance the accuracy of face-to-skull prediction.

Keywords: face-to-head prediction; statistical shape modelling; head-to-skull prediction; biomechanical head simulation; partial least squares regression; PLSR; principal component analysis; PCA.

DOI: 10.1504/IJBET.2024.140689

International Journal of Biomedical Engineering and Technology, 2024 Vol.46 No.1, pp.1 - 26

Received: 18 Oct 2023
Accepted: 14 Dec 2023
Published online: 30 Aug 2024 *

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