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


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


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




    ISMRM 2019

    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 (T1 and 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.