Dr. Selma Metzner
Vattenfall

Bayesian Data Analysis for quantitative Magnetic Resonance Fingerprinting
(English)

Kolloquiumsvortrag – Sonderforschungsbereich 876 "Verfügbarkeit von Information durch Analyse unter Ressourcenbeschränkung"

Donnerstag, 02.06.2022, 16:15 – 17:45 Uhr
Hörsaal OH14/E23

Gastgeber: Prof. Dr. Katharina Morik

Zusammenfassung
Gastgeber: Prof. Katja Ickstadt

Abstract - Magnetic Resonance Imaging (MRI) is a medical imaging technique which is widely used in clinical practice. Usually, only qualitative images are obtained. The goal in quantitative MRI (qMRI) is a quantitative determination of tissue- related parameters. In 2013, Magnetic Resonance Fingerprinting (MRF) was introduced as a fast method for qMRI which simultaneously estimates the parameters of interest. In this talk, I will present main results of my PhD thesis in which I applied Bayesian methods for the data analysis of MRF. A novel, Bayesian uncertainty analysis for the conventional MRF method is introduced as well as a new MRF approach in which the data are modelled directly in the Fourier domain. Furthermore, results from both MRF approaches will be compared with regard to various aspects.