Abstract #1632

CMAPSS-NET: Deep-Learning Based Reconstruction of 3D Magnetization-Prepared GRE with Complementary Phase-Cycling Acquisition

Ramin Jafari¹, Can Wu², Yansong Zhao³, Victor Murray², and Qi Peng⁴

¹Philips Healthcare, New York, NY, United States, ²Memorial Sloan Kettering Cancer Center, New York, NY, United States, ³Philips Healthcare, Boston, MA, United States, ⁴Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY, United States

Synopsis

Keywords: Quantitative Imaging, Image Reconstruction

Deep learning enables efficient reconstruction of 3D Magnetization-Prepared GRE with Complementary Phase-Cycling to remove both undersampling artifacts as well as T1 contamination associated with this type of acquisition only requiring half the acquisition time compared to current standard technique.

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