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Abstract #3806

CNN-based synthesis of T1, T2 and PD parametric maps of the brain with a minimal input feeding

Elisa Moya-Sáez1, Óscar Peña-Nogales1, Santiago Sanz-Estébanez1, Rodrigo de Luis-Garcia1, and Carlos Alberola-López1
1Laboratorio de Procesado de Imagen, Universidad de Valladolid, Valladolid, Spain

Parametric MR maps (T1, T2 and PD) not only play a key role in quantitative imaging but they also have the capability of synthesizing any modality. However, their direct acquisition is hardly used in practice due to the need of lengthy relaxometry protocols. Synthetic MRI is a surrogate; however, no approach has been described to synthesize these maps out of a small number of customary sequences. In this work we synthesize T1, T2 and PD maps out of a T1- and a T2-weighted image using a CNN trained only with synthetic data. Our approach yields realistic maps from real data.

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