Hannover 2020 – wissenschaftliches Programm
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Q 29.8: Vortrag
Mittwoch, 11. März 2020, 12:45–13:00, f442
Optimal Control Methods applied in Magnetic Resonance Fingerprinting — •Amanda Nicotina and Steffen Glaser — Technische Universität München
A method of parameter identification via Magnetic Resonance (MR) is called MR Fingerprinting (FP) recognition. The basic methods of fingerprint recognition are: fingerprinting recording, creation of data base and recognition process with a search algorithm. This can be applied to systems that can be mapped by unique measurable properties. For example, brain tissue identification using MRI. This system can be static or dynamic (influenced by external fields). In the latter, the elements of the data base consist of the time evolved observable under the action of some external field. Since the dictionary, formed by the data base, depends strongly on the external fields, designing them is crucial for the FP process. Therefore, optimal control techniques can be combined with standard FP process for better precision. The Optimal Fingerprinting Process (OFP) allows us to maximize the efficiency of the identification and minimize parameter error. This method will be used to verify relaxation parameters of a spin 1/2 spin particle. The goal is to apply OFP to improve the contrast. Therefore, having better recognition between different brain tissues, for example, the different relaxation values for white matter and gray matter in healthy brain and in Multiple Sclerosis (MS) patients.