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Abstract #3378

Derivation of liver R2* and B0 maps from dual-echo MR images via deep learning

Yan Wu1, Yongwook Kee1, Marc Alley1, John Pauly2, Lei Xing1, and Shreyas Vasanawala1
1Stanford University, Stanford, CA, United States, 2Stanford University, Stanford University, CA, United States


Quantitative R2* map is an important liver disease indicator. However, the availability of R2* map is limited by the long scan time. In this study, we present a new paradigm to predict R2* and B0 maps from dual echo images. A self-attention deep convolutional neural network is trained and validated, where promising accuracy has been obtained. The proposed quantitative parametric mapping approach has a potential to eliminate the necessity for additional data acquisition other than clinical routine.

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