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Abstract #4434

Reliable Low-Field B0-Maps by Deep Learning with Physical Constraints

David Schote1, Lukas Winter1, Christoph Kolbitsch1, and Andreas Kofler1
1Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany

Synopsis

Keywords: System Imperfections: Measurement & Correction, Low-Field MRI, B0-field mapHeavy B0-field inhomogeneities in low-field MRI can lead to geometric distortions in the reconstruction, if not compensated. We simulated low-field data to evaluate different approaches for estimating the field map from phase difference maps. By using spherical harmonic basis functions as physical constraints in our neural network approach we could improve the estimation of B0-field maps compared to other network architectures and methods not involving neural networks.

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