Abstract #2827

Quad-contrast imaging with deep learning-powered reconstruction: 2-minute neuro-evaluation

Sooyeon Ji¹, Doohee Lee¹, Se-Hong Oh², and Jongho Lee¹

¹Electrical and Computer Engineering, Seoul National University, Seoul, Korea, Republic of, ²Biomedical Engineering, Hankuk University of Foreign Studies, Seoul, Korea, Republic of

A 2D multi-contrast sequence with deep learning-powered reconstruction is developed to generate four contrast images (PDw, T₁w, T₂w, and FLAIR) and two quantitative maps (T₁and T₂) in 2 minutes of scan time. For the reconstruction, a new deep learning method that assures both data consistency and image fidelity is applied with the joint reconstruction of the quad-contrast k-space data.

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