Introduction
Welcome to the website for the master seminar on machine learning in neuroimaging. The field of neuroimaging deals with computational methods for the quantitative study of the the central nervous system. Today, there exists a multitude of different imaging modalities like magnetic resonance imaging (MRI) or fluorodeoxyglucose positron emission tomography (FDG-PET), allowing for non-invasive analyses of the structure and functionality of the human brain. The gained insights are of high relevance not only for a better understanding of cognitive functions of healthy individuals but also for the study of neurological disorders like dementia or multiple sclerosis.
In this seminar, we discuss recent scientific publications of machine learning algorithms in the context of neuroimaging and brain disorders. This includes the latest advances in deep learning-based image processing, medical image analysis, and modern statistical methods.
For details, click on the seminar for the respective semester.