A Ring Artifact Correction Method: Validation by Micro-CT Imaging with Flat-Panel Detectors and a 2D Photon-Counting Detector

Eldib, Mohamed Elsayed; Hegazy, Mohamed A. A.; Mun, Yang Ji; Cho, Myung Hye; Cho, Min Hyoung; Lee, Soo Yeol

doi:10.3390/s17020269

Cited by 28 publications

(17 citation statements)

References 23 publications

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“…Important work was done to analyze visible singularities for ROI (or local) tomography (e.g., [12,25,28,46,50]). However, we are not aware of any reference where a microlocal explanation for the ring artifact in ROI CT was provided, although researchers are well aware of the ring itself (e.g., [7,10]). We are also not aware of microlocal analyses of more general imaging setups, such as the nonstandard one presented in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

Analyzing Reconstruction Artifacts from Arbitrary Incomplete X-ray CT Data

Borg

Frikel²,

Jørgensen

et al. 2018

SIAM J. Imaging Sci.

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This article provides a mathematical analysis of singular (nonsmooth) artifacts added to reconstructions by filtered backprojection (FBP) type algorithms for X-ray CT with arbitrary incomplete data. We prove that these singular artifacts arise from points at the boundary of the data set. Our results show that, depending on the geometry of this boundary, two types of artifacts can arise: object-dependent and object-independent artifacts. Object-dependent artifacts are generated by singularities of the object being scanned and these artifacts can extend along lines. They generalize the streak artifacts observed in limited-angle tomography. Object-independent artifacts, on the other hand, are essentially independent of the object and take one of two forms: streaks on lines if the boundary of the data set is not smooth at a point and curved artifacts if the boundary is smooth locally. We prove that these streak and curve artifacts are the only singular artifacts that can occur for FBP in the continuous case. In addition to the geometric description of artifacts, the article provides characterizations of their strength in Sobolev scale in certain cases. The results of this article apply to the well-known incomplete data problems, including limitedangle and region-of-interest tomography, as well as to unconventional X-ray CT imaging setups that arise in new practical applications. Reconstructions from simulated and real data are analyzed to illustrate our theorems, including the reconstruction that motivated this work-a synchrotron data set in which artifacts appear on lines that have no relation to the object.

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Section: Introductionmentioning

confidence: 99%

Analyzing Reconstruction Artifacts from Arbitrary Incomplete X-ray CT Data

Borg

Frikel²,

Jørgensen

et al. 2018

SIAM J. Imaging Sci.

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show abstract

“…Some of these methods assume the presence of a specific high-frequency component that is directly related to the ring artifacts. Therefore, they aim to filter out the artifacts using low pass filters [ 12 , 13 , 14 , 15 ]. Most of these, however, fail to remove the strong artifacts related to dead detector elements or damaged areas on the scintillator, in which case they create an extra band around the original ring [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Complete Ring Artifacts Reduction Procedure for Lab-Based X-ray Nano CT Systems

Šalplachta

Zikmund

Zemek

et al. 2021

Sensors

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In this article, we introduce a new ring artifacts reduction procedure that combines several ideas from existing methods into one complex and robust approach with a goal to overcome their individual weaknesses and limitations. The procedure differentiates two types of ring artifacts according to their cause and character in computed tomography (CT) data. Each type is then addressed separately in the sinogram domain. The novel iterative schemes based on relative total variations (RTV) were integrated to detect the artifacts. The correction process uses the image inpainting, and the intensity deviations smoothing method. The procedure was implemented in scope of lab-based X-ray nano CT with detection systems based on charge-coupled device (CCD) and scientific complementary metal–oxide–semiconductor (sCMOS) technologies. The procedure was then further tested and optimized on the simulated data and the real CT data of selected samples with different compositions. The performance of the procedure was quantitatively evaluated in terms of the artifacts’ detection accuracy, the comparison with existing methods, and the ability to preserve spatial resolution. The results show a high efficiency of ring removal and the preservation of the original sample’s structure.

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“…Removing ring artifacts is more feasible in sinogram domain, since the defective pixels always appears as single or multiple stripe artifacts. Various filters, such as center-weighted median filter [12], wavelet-Fourier filter [13] and Gaussian filter [14] have been utilized in removing ring artifacts. Podgorsak et al proposed a median filtering-based method [19] based on the assumption that the values measured by the same defective pixel have same attenuation against the ideal values.…”

Section: Introductionmentioning

confidence: 99%

Ring Artifacts Reduction in CBCT: Pixels Detection and Patch Based Correction

Zhao¹,

Li²,

Luo³

2019

Molecular &Amp; Cellular Biomechanics

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The ring artifacts introduced by the defective pixels with non-linear responses in the high-resolution detector, have a great impact on subsequent processing and quantitative analysis of the reconstructed images. In this paper, a multistep method is proposed to suppress the ring artifacts of micro CT images, which firstly locates the positions of the defective pixels in the sinogram, and then corrects the corresponding value in the projections. Since the defective pixels always appear as vertical stripes in the sinogram, a horizontal curve is derived by summing the pixel values along vertical direction, thus the abrupt segments related to the defective stripes are enhanced notably, and a proportion coefficient based on the second derivative of the curve is taken as the indicator for the position and the severity of the defective pixels. Then, the detected defective pixels in the sinogram are transferred and relocated in the projections, an improved 3D block matching filtering (BM3D) algorithm is applied to restore the defective pixels in corresponding projection images. In the end, the tomographic images are reconstructed from the corrected projections. In the experiment, a small piece of the motherwort's rhizome and a part of a mouse's lung are imaged by micro-CT, and the result shows that, compared with the other four state-of-art methods, the proposed method has a great reduction on the ring artifacts of the reconstructed images, and makes less impact in spatial resolution and contrast in the same time.

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A Ring Artifact Correction Method: Validation by Micro-CT Imaging with Flat-Panel Detectors and a 2D Photon-Counting Detector

Cited by 28 publications

References 23 publications

Analyzing Reconstruction Artifacts from Arbitrary Incomplete X-ray CT Data

Analyzing Reconstruction Artifacts from Arbitrary Incomplete X-ray CT Data

Complete Ring Artifacts Reduction Procedure for Lab-Based X-ray Nano CT Systems

Ring Artifacts Reduction in CBCT: Pixels Detection and Patch Based Correction

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