Tina Anne Schuetz

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In the present work, a novel computational framework for variational non-rigid image registration is discussed. The fundamental aim is to provide an alternative to approximate approaches based on successive convolution, which have gained great popularity in recent years, due to their linear complexity and ease of implementation. An optimise-then-discretise(More)
A novel hybrid continuum-discrete model to simulate tumour growth on a cellular scale is proposed. The lattice-based spatiotemporal model consists of reaction-diffusion equations that describe interactions between cancer cells and their microenvironment. The fundamental ingredients that are typically considered are the nutrient concentration, the(More)
Glioblastomas are highly malignant brain tumours. Mathematical models and their analysis provide a tool to support the understanding of the development of these tumours as well as the design of more effective treatment strategies. We have previously developed a multiscale model of glioblastoma progression that covers processes on the cellular and molecular(More)
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