Abstract #1828

3D Silent Parameter Mapping: Further refinements & quantitative assessment

Florian Wiesinger^1,2, 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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