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Abstract #1828

3D Silent Parameter Mapping: Further refinements & quantitative assessment

Florian Wiesinger1,2, Graeme McKinnon3, Sandeep Kaushik1, Ana Beatriz Solana1, Emil Ljungberg2, Mika Vogel1, Naoyuki Takei4, Rolf Schulte1, Carolin Pirkl1, Cristina Cozzini1, Laura Nuñez-Gonzalez5, Juan A. Hernandez Tamames5, and Mathias Engström6
1GE Healthcare, Munich, Germany, 2IoPPN, Department of Neuroimaging, King's College London, London, United Kingdom, 3GE Healthcare, Waukesha, WI, United States, 4GE Healthcare, Hino, Japan, 5Erasmus MC, Rotterdam, Netherlands, 6GE Healthcare, Stockholm, Sweden

Here we present further improvements of a 3D Silent Parameter Mapping method in terms of Deep Learning image reconstruction and synthetic CT image conversion. We evaluated its quantitative accuracy using the NIST/ISMRM phantom and illustrate healthy volunteer results at 1.5T and 3T.

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