Image-based validation of computational models for vascularized solid tumour growth


In tumor modeling we focus on developing new approaches for a comprehensive validation of predictive models of tumor growth using image information.

While both, model development and tumor imaging, have seen rapid progress in recent years, rather little progress has been made so far towards assimilating experimental data into tumor models. We address the full integration of measurement and simulation by focusing on the initialization problem and the development of new methods for a fast image-based inference by combining generative models of disease progression with efficient techniques from machine learning. We rely primarily on functional imaging data from of small animal models for acquiring multimodal time series of tumor progression in vivo.

Participants: Prof. Bjoern Menze, Prof. Dr. Sven Hirsch, Prof. Gábor Székely


NCCR Co-Me Animal Imaging Center, ETH Zurich (Prof. Rudin )