Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Soft tissue modelling and facial movement simulation using the finite element method

Lu, Yongtao 2010. Soft tissue modelling and facial movement simulation using the finite element method. PhD Thesis, Cardiff University.

[img] PDF - Accepted Post-Print Version
Download (29MB)


This thesis presents a framework for soft tissue modelling, facial surgery simulation, and facial movement synthesis based on the volumetric finite element method. Assessment of facial appearance pre- and post-surgery is of major concern for both patients and clinicians. Pre-surgical planning is a prerequisite for successful surgical procedures and outcomes. Early computer-assisted facial models have been geometrically based. They are computationally efficient, but cannot give an accurate prediction for facial surgery simulation. Therefore, in this thesis, the emphasis is placed on physically-based methods, especially the finite element technique. To achieve realistic surgery simulation, soft tissue modelling is of crucial importance. Thus, in this thesis, considerable effort has been directed to develop constitutive equations for facial skeletal muscles. The skeletal muscle model subsequently developed is able to capture the complex mechanical properties of skeletal muscle, which are active, quasi-incompressible, fibre-reinforced and hyperelastic. In addition, to improve the characterisation of in-vivo muscle behaviour, a technique has been developed to visualise the internal fibre arrangement of skeletal muscle using the FEM-NURBS method, which is the combination of the finite element method and the non-uniform rational B-spline solid mathematical representation. Another principal contribution made in this thesis is the three-dimensional finite element facial model, which can be used for the simulations of facial surgery and facial movement. The procedure of one cranio-facial surgery is simulated by using this facial model and the numerical predictions show a good agreement with the patient post-surgical data. In addition, it would be very helpful to also simulate the facial movement and facial expressions. In this thesis, two facial expressions (smile and disgust) and the mouth opening are simulated to assess the post-surgical appearance and test the muscle-driven facial movement simulation method.

Item Type: Thesis (PhD)
Status: Unpublished
Schools: Advanced Research Computing @ Cardiff (ARCCA)
Subjects: R Medicine > RK Dentistry
ISBN: 9781303195570
Funders: ARUP
Date of First Compliant Deposit: 30 March 2016
Last Modified: 15 Sep 2014 12:33

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics