Deep Learning-based Magnetic Resonance Fingerprinting
Elisabeth Hoppe, Pattern Recognition Lab / Magnetic Resonance Imaging / Friedrich-Alexander-Universität Erlangen-Nürnberg
Live stream: https://www.conf.dfn.de/stream/nr5h8pp6e87k3
Abstract: “Magnetic Resonance Fingerprinting (MRF) is a recently developed quantitative Magnetic Resonance Imaging technique. The sequence acquires multiple image contrasts, resulting in so-called fingerprints for every voxel by changing acquisition parameters. These fingerprints are used to reconstruct quantitative maps containing information about the physical state of the underlying tissues. This talk first will give an introduction to the quantitative acquisition and the State-of-the-art reconstruction methods. Further, it will give an overview about Deep Learning applications for MRF reconstruction and show how the efficient Deep Learning-based reconstruction can be achieved.“
