APA (7th ed.) Citation

Stokes, C., Bonfanti, M., Li, Z., Xiong, J., Chen, D., Balabani, S., & Díaz-Zuccarini, V. (2021). A novel MRI-based data fusion methodology for efficient, personalised, compliant simulations of aortic haemodynamics. Journal of biomechanics, 129, 110793. https://doi.org/10.1016/j.jbiomech.2021.110793

Chicago Style (17th ed.) Citation

Stokes, Catriona, Mirko Bonfanti, Zeyan Li, Jiang Xiong, Duanduan Chen, Stavroula Balabani, and Vanessa Díaz-Zuccarini. "A Novel MRI-based Data Fusion Methodology for Efficient, Personalised, Compliant Simulations of Aortic Haemodynamics." Journal of Biomechanics 129 (2021): 110793. https://doi.org/10.1016/j.jbiomech.2021.110793.

MLA (9th ed.) Citation

Stokes, Catriona, et al. "A Novel MRI-based Data Fusion Methodology for Efficient, Personalised, Compliant Simulations of Aortic Haemodynamics." Journal of Biomechanics, vol. 129, 2021, p. 110793, https://doi.org/10.1016/j.jbiomech.2021.110793.