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Abstract #2639

Dynamic distortion correction of ME-EPI using learning-based single-scan multi-echo blip up-down acquisition (ME-BUDA)

Nuowei Ge1, Qinqin Yang1, Zejun Wu1, Jianfeng Bao2, Zhigang Wu3, Congbo Cai1, and Shuhui Cai1
1Department of Electronic Science, Xiamen University, Xiamen, China, 2Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China, 3Clinical & Technical Solutions, Philips Healthcare, Shenzhen, China

Synopsis

Keywords: Artifacts, Artifacts, Distortion correction, ME-EPI

Motivation: Multi-echo (ME) fMRI approaches based on ME-EPI acquisition achieve higher BOLD sensitivity and reproducibility than traditional EPI. However, ME-EPI suffers from severe image distortion.

Goal(s): To develop a technique to correct ME-EPI distortion artifacts in single scan.

Approach: We developed a deep learning-based technique to correct ME-EPI distortion artifacts using single-scan multi-echo blip up-down acquisition (ME-BUDA). The proposed method was suitable for both spin- and gradient-echo-based EPI and was validated in simulation, human brain and additional dynamic imaging experiments.

Results: For simulation experiment, the PSNR and SSIM were 33.31 and 0.98, respectively. For in vivo dynamic imaging, the temporal SNR increased by 75%.

Impact: The ME-BUDA method can reliably correct the geometric distortion of dynamic ME-EPI images without additional information, ensuring the distortion-free, real-time, and high-quality ME-fMRI analysis of important function regions.

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