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Abstract #4548

T2w-FLAIR generation through deep-learning using distortion-free PSF-EPI DWI

Zhangxuan Hu1, Zhe Zhang2, Yishi Wang3, Yajing Zhang4, and Hua Guo1
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2China National Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China, 3Philips Healthcare, Beijing, China, 4MR Clinical Science, Philips Healthcare (Suzhou), Suzhou, China

MRI examinations usually contain multi-contrast images, which may share redundant information. For example, T2w-FLAIR contrast relies on the property of T2 relaxation and water component of the tissue, which also present in T2- and diffusion-weighted images. T2w-FLAIR acquisition is usually lengthy due to the long inversion time. In this study, point-spread-function (PSF) encoded EPI (PSF-EPI) DWI and T2-weighted images were used to generate T2w-FLAIR images by taking the advantages of high-resolution and distortion-free of PSF-EPI. This method has the potential to improve the acquisition efficiency of MRI.

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