Image-Based Elastography Using Non-Rigid Medical Image Registration
Supervisor: Professor Alejandro Frangi

Medical image-based elastography aims at non-invasive estimation of in-vivo mechanical property estimation of human tissues. The goal is to be able to ascertain the value of elastic properties of tissues like vascular walls or the myocardium as markers of disease and disease state. 

This particular project will focus on assessing the vascular properties of pulsating cerebral aneurysms. The candidate will research the state-of-the-art in computational models of the constitutive elastic properties of cerebral aneurysms and, subsequently, will perform a computational comparison between the various models of their ability to represent the true tissue behaviour versus its inherent modelling and computational complexity. The project will provide conclusions and suggestions as to which model could be used for material parameter estimation from medical data.

me-pgadmit@sheffield.ac.uk
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