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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