Adaptive patch-based ring artifacts removal for photon-counting CT

Photon-counting computed tomography (PCCT) is superior in providing better CT image contrast than traditional CT technology. However, noticeable ring artifacts are more likely caused by the imperfect functioning of photon-counting detectors. This study proposes an efficient ring artifacts correction approach based on the unique characteristics of unwanted components in multi-domains. First, a patch-based signed statistic is utilized to identify the aberrant patches in the frequency space data of the sinogram data. Then, the adaptive patch (AP) filter and plausible patch filtering strategies are developed to correct undesirable patches. Third, an adaptive stripe (AS) filter is suggested in the spatial space to enhance the AP-filtered sinogram data. The experimental results indicate that the proposed methods outperform the state-of-the-art methods in artifact removal and structure preservation.

Authors

Publication Details

Journal
Optics Express
Published
2024-11-27
DOI
https://doi.org/10.1364/oe.538515
Citations
2
Primary Topic
Advanced X-ray and CT Imaging
Type
article
Field-Weighted Citation Impact
0.37
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article

Adaptive patch-based ring artifacts removal for photon-counting CT

Dimeng Xia, Shusen Zhao, Xiangyuan Liu, Fengwei An et al.
2 citations
Optics Express
Advanced X-ray and CT Imaging
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article

Adaptive patch-based ring artifacts removal for photon-counting CT

Dimeng Xia, Shusen Zhao, Xiangyuan Liu, Fengwei An, Weibin Zhang
article en
2 citations

Abstract

Photon-counting computed tomography (PCCT) is superior in providing better CT image contrast than traditional CT technology. However, noticeable ring artifacts are more likely caused by the imperfect functioning of photon-counting detectors. This study proposes an efficient ring artifacts correction approach based on the unique characteristics of unwanted components in multi-domains. First, a patch-based signed statistic is utilized to identify the aberrant patches in the frequency space data of the sinogram data. Then, the adaptive patch (AP) filter and plausible patch filtering strategies are developed to correct undesirable patches. Third, an adaptive stripe (AS) filter is suggested in the spatial space to enhance the AP-filtered sinogram data. The experimental results indicate that the proposed methods outperform the state-of-the-art methods in artifact removal and structure preservation.

Optics ExpressVol. 33(1)
Openalex Percentile: Top 42%
Advanced X-ray and CT Imaging
0.37
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