Abstract
Nowadays, there are different medical imaging techniques to collect data about the progression of Alzheimer's disease in a patient's brain. These data describe different phenomena which are still not understood from a biological point of view. How can these data sets be combined in a mathematical model to simulate the evolution of such a neurodegenerative disease in a computer? In this snapshot, we present one possible approach to address this task with the help of graph theory and partial differential equations.