Abstract #4043

Deep Learning Reconstruction for 4-fold Accelerated 2DFSE Imaging: optimization of variable density undersampling

Michael Carl¹, Rafi Brada², Nir Mazor², Daniel V Litwiller³, and Maggie Fung⁴

¹GE Healthcare, San Diego, CA, United States, ²GE Research, Herzliya, Israel, ³GE Healthcare, Denver, CO, United States, ⁴GE Healthcare, New York, NY, United States

Synopsis

Keywords: Machine Learning/Artificial Intelligence, Machine Learning/Artificial IntelligenceIn this work we use variable-density prospective undersampling of the phase-encode k-space lines (ky) in 2D fast spin-echo (2DFSE) followed by deep learning (DL) reconstruction. We were able to achieve an acceleration of R=4 while maintaining high image quality.

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