2021
DOI: 10.1007/s00138-021-01224-3
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Images denoising for COVID-19 chest X-ray based on multi-resolution parallel residual CNN

Abstract: Chest X-ray (CXR) is a medical imaging technology that is common and economical to use in clinical. Recently, coronavirus (COVID-19) has spread worldwide, and the second wave is rebounding strongly now with the coming winter that has a detrimental effect on the global economy and health. To make pre-diagnosis of COVID-19 as soon as possible, and reduce the work pressure of medical staff, making use of deep learning networks to detect positive CXR images of infected patients is a critical step. However, there a… Show more

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Cited by 8 publications
(1 citation statement)
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“…Recent image restoration methods for X-ray images have shown successful performance by using deep learning schemes. [8][9][10] Specifically, several works 8,9 show that deep convolutional neural networks (CNNs) can be used to remove noise in CXR images. Furthermore, it was shown that scatter effects in CXR images can also be reduced using CNNs.…”
Section: Introductionmentioning
confidence: 99%
“…Recent image restoration methods for X-ray images have shown successful performance by using deep learning schemes. [8][9][10] Specifically, several works 8,9 show that deep convolutional neural networks (CNNs) can be used to remove noise in CXR images. Furthermore, it was shown that scatter effects in CXR images can also be reduced using CNNs.…”
Section: Introductionmentioning
confidence: 99%