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Title: Detector shifting and deep learning based ring artifact correction method for low-dose CT.
Authors: Liu, Yuedong; Wei, Cunfeng; Xu, Qiong
Abstract: In x-ray computed tomography (CT), the gain inconsistency of detector units leads to ring artifacts in the reconstructed images, seriously destroys the image structure, and is not conducive to image recognition. In addition, to reduce radiation dose and scanning time, especially photon counting CT, low-dose CT is required, so it is important to reduce the noise and suppress ring artifacts in low-dose CT images simultaneously.
Publication: Medical physics, 2023, Vol 50, Issue 7, p4308
ISSN: 2473-4209
Publication type: Journal Article
DOI: 10.1002/mp.16225

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Detector shifting and deep learning based ring artifact correction method for low-dose CT.