Predictive and personalized models of cancer can enhance the understanding of the disease and aid in the development of more effective patient-specific treatment strategies. This thesis deals with computational approaches for a group of continuum-based multiphase tumor growth models. Three different vascular model types are developed with a homogenized, discrete and hybrid representation of the vascular network, respectively. The hybrid variant, which relies only on data from non-invasive imaging, is examined in more detail for modeling perfusion through solid tumors.
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Predictive and personalized models of cancer can enhance the understanding of the disease and aid in the development of more effective patient-specific treatment strategies. This thesis deals with computational approaches for a group of continuum-based multiphase tumor growth models. Three different vascular model types are developed with a homogenized, discrete and hybrid representation of the vascular network, respectively. The hybrid variant, which relies only on data from non-invasive imagin...
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