The overall aim of the project is to develop a mathematical framework to quantitatively predict the tissue quality by using advanced imaging techniques, microstructural analysis, nonlinear homogenisation and in-situ experimentation. To achieve the aim the project will address a number of challenges:

1. Recent technologies have permitted imaging at very small length scales. However, conversion of images to models (required for analysis) continues to remain a challenge. Both low contrast (including other nearby and similar features) and noise can fail existing segmentation methods, while current registration models (e.g. the widely used optical flow based model) may not be capable of dealing with large deformation. We are researching to establish a reliable multi-modality image registration model. We are developing a robust local segmentation model with the help of registration for automatic localisation, capable of dealing with structures for organ, tissue and cell level segmentation.
2. The relationships that link microstructure to macroscopic response are required to predict tissue quality. With rapid development of microscopic and even sub-micro imaging approaches, the microarchitecture can provide crucial information on tissue quality. However, which key parameters of the microarchitecture are the primary determinants of tissue quality remains unclear. We are investigating to find which indices of tissue microstructure provide a link to macroscopic bone quality, with the integration of various patient parameters (e.g. gender, age, lifestyle and drug treatments).
3. Several yield, damage and failure criteria have been employed for bone at the apparent level. Apart from a few, almost all of these are based on existing criteria for engineering materials and do not take into account changes in the bone microstructure. It is apparent that the nonlinear constitutive model of the tissue’s solid phase will be simpler than the nonlinear response at the macro level due to the tissue’s complex microarchitecture. Our research will establish how nonlinearity at the microscopic level affects the macroscopic tissue behaviour.
4. Invariably, samples used for analysis of microarchitecture are not the same as those tested mechanically. It has now become possible to examine the microarchitecture of tissue samples in a loaded state. Our research will conduct detaled validation at different scales.