Optoelectronics Letters, Volume. 18, Issue 1, 54(2022)

Motion artifact correction for MR images based on convolutional neural network

Bin ZHAO1...2, Zhiyang LIU1,2, Shuxue DING1,2,3, Guohua LIU1,2, Chen CAO4, and Hong WU12,* |Show fewer author(s)
Author Affiliations
  • 1College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China
  • 2Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology, Nankai University, Tianjin 300350, China
  • 3School of Artificial Intelligence, Guilin University of Electronic Technology, Guilin 541004, China
  • 4Department of Medical Imaging, Tianjin Huanhu Hospital, Tianjin 300350, China
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    Magnetic resonance imaging (MRI) is a common way to diagnose related diseases. However, the magnetic resonance (MR) images are easily defected by motion artifacts in their acquisition process, which affects the clinicians' diagnosis. In order to correct the motion artifacts of MR images, we propose a convolutional neural network (CNN)-based method to solve the problem. Our method achieves a mean peak signal-to-noise ratio (PSNR) of (35.212±3.321) dB and a mean structural similarity (SSIM) of 0.974 ± 0.015 on the test set, which are better than those of the comparison methods.

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    ZHAO Bin, LIU Zhiyang, DING Shuxue, LIU Guohua, CAO Chen, WU Hong. Motion artifact correction for MR images based on convolutional neural network[J]. Optoelectronics Letters, 2022, 18(1): 54

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    Paper Information

    Received: May. 21, 2021

    Accepted: Sep. 29, 2021

    Published Online: Jan. 20, 2023

    The Author Email: Hong WU (wuhong@nankai.edu.cn)

    DOI:10.1007/s11801-022-1084-z

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