ARTIFACT AND/OR NOISE REDUCTION FOR MAGNETIC RESONANCE FINGERPRINTING DATA BASED ON A NEURAL NETWORK

Methods and devices for fingerprinting magnetic resonance imaging are described. The method comprises acquiring a first sequence of MR data (2000) within a region of interest using a fingerprinting magnetic resonance pulse sequence; inputting the first sequence of MR data to a neural network (3000);...

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Bibliographic Details
Main Authors Maier, Andreas, Xu, Yiling, Hoppe, Elisabeth, Koerzdoerfer, Gregor
Format Patent
LanguageEnglish
French
German
Published 28.07.2021
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
MEASURING
MEASURING ELECTRIC VARIABLES
MEASURING MAGNETIC VARIABLES
PHYSICS
TESTING
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Summary:Methods and devices for fingerprinting magnetic resonance imaging are described. The method comprises acquiring a first sequence of MR data (2000) within a region of interest using a fingerprinting magnetic resonance pulse sequence; inputting the first sequence of MR data to a neural network (3000); outputting a second sequence of MR data from the neural network, wherein the second sequence of MR data have reduced undersampling/aliasing artifacts and/or noise if compared to the first sequence of MR data (4000); determining values of at least one quantitative parameter for the region of interest based on the second sequence of MR data (4000); and constructing a quantitative parameter map of the at least one quantitative parameter for the region of interest based on the determined values.
Bibliography:Application Number: EP20200153176