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Model Based Medical Imaging

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Model Based Medical Imaging

All medical imaging modalities that infer spatially distributed properties of tissues given measured values of propogated radiation make use of mathematical models of physical laws. In some cases such as line integrals of densities these models are only implicit. By contrast a number of questions in medical imaging require explicit models, controlled by input parameters, whence the imaging process can be cast as an inverse problem in the inference of the model parameters given the data. Several CMIC projects are in progress both for developing the computational aspects of the modelling problem using techniques such as Finite Elements and Boundary Elements, and for the inverse problem. This talk will give an overview of this work, and including aspects of Bayesian priors, multimodality and approximation error theory.

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