Optoelectronics Letters, Volume. 18, Issue 1, 54(2022)
Motion artifact correction for MR images based on convolutional neural network
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
Received: May. 21, 2021
Accepted: Sep. 29, 2021
Published Online: Jan. 20, 2023
The Author Email: Hong WU (wuhong@nankai.edu.cn)