| CPC G01R 33/5608 (2013.01) [A61B 5/055 (2013.01); A61B 5/7267 (2013.01); G01R 33/4828 (2013.01); G06N 3/02 (2013.01)] | 20 Claims |
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1. A computer-implemented method, performed using one or more processors and a non-transitory computer-readable storage medium, for determining a fat-reduced magnetic resonance (MR) image of a tissue under examination that has, apart from other tissue constituents, two fat constituents of different resonance frequency, the method comprising:
providing a first MR image, which has, apart from the other tissue constituents, MR signals from only one of the two fat constituents;
applying the first MR image to a trained artificial neural network, which was trained by first MR training data as input data, the training data including, apart from the other tissue constituents, MR signals from only the one of the two fat constituents, and using second MR training data as a base knowledge, the second MR training data including, apart from the other tissue constituents, no MR signals from the two fat constituents; and
determining an MR output image from the trained artificial neural network, to which the first MR image was applied, as a fat-reduced MR image, wherein the fat-reduced MR image includes, apart from the other tissue constituents, no MR signals from the two fat constituents.
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