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Abstract #3543

Enhanced One-minute EPImix Brain MRI Scans with distortion correction Based on supervised GAN model

Haining Wei1, Jiang Liu2, Enhao Gong3, Stefan Skare4, and Greg Zaharchuk5
1Tsinghua University, Beijing, China, 2The Johns Hopkins University, Baltimore, MD, United States, 3Subtle Medical Inc., Menlo Park, CA, United States, 4Karolinska Institutet, Stockholm, Sweden, 5Stanford University, Stanford, CA, United States

EPImix is a one-minute full brain magnetic resonance exam using a multicontrast echo-planar imaging (EPI) sequence, which can generate six contrasts at a time. However, the low resolution and signal-to-noise ratio impeded its application. And EPI distortion makes it harder to improve the quality of imaging. In this study, we applied topup for distortion correction and propose a supervised deep learning model to enhance the EPImix images. We test the GRE, T2, T2FLAIR images on network and analyze the peak signal to noise ratio and structural similarity results. The results suggest that the proposed method can effectively enhance EPImix images.

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