Removing ring artefacts in CT images via unidirectional relative variation model

Huo, Qirun; Li, Jianwu; Lu, Yao

doi:10.1049/el.2016.2692

Cited by 10 publications

(7 citation statements)

References 9 publications

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“…In order to facilitate visual analysis of removing artifacts, the sizes of the images in Cartesian coordinates and polar coordinates were set as 512 × 512 and 360 × 360, respectively. For a comprehensive and fair comparison, we included the results of applying the ring correction in polar coordinate (RCP), and the URTV model on our simulated and real images, respectively. Figure shows the intermediate results illustrating the effectiveness of two important steps based on the proposed scheme.…”

Section: Resultsmentioning

confidence: 99%

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Removing ring artifacts in cone‐beam CT via TV‐Stokes and unidirectional total variation model

Wang

2019

Medical Physics

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Purpose: It often happens that cone-beam corrupted tomography (CBCT) images have some ring artifacts due to the inconsistent response of detector pixels. Removing ring artifacts in CBCT images without impairing the image quality is critical. The purpose of this study is to implement a whole new method of removing ring artifacts in CBCT images based on TV-Stokes denoising equation and unidirectional total variation (UTV). Methods: This method is based on the polar coordinates, where the ring artifacts are shown as horizontal parallel stripes. To begin with, we design a UTV model with the constraint of zero divergence condition to only smooth vertical tangent vectors, and keep horizontal tangent vectors unchanged. In turn, the corresponding smooth normal vectors can be obtained. Next, in order to reconstruct the clean image that fits the obtained normal vectors, the UTV model about the potential clean image is added to the original TV-Stokes denoising equation. Results: Our method was applied to simulated data and real corrupted data to verify its performance. High-quality corrected images without ring artifacts were obtained. In the simulated experiments, our method is not only able to obtain the most complete corrected images, but also capable of acquiring the best quantitative assessments among several different methods. In the experiments of real data, the proposed method was effective in removing ring artifacts and in preserving the original details. Comparative results on several experiments illustrated that our algorithm corrects ring artifacts effectively and outperforms the two compared methods on objective indices and subjective image quality. Conclusions: Benefiting from the TV-Stokes equation and the UTV model, the proposed scheme can be effectively applied to remove ring artifacts in CBCT images, simultaneously preserving the original image details and structure well. Furthermore, this new algorithm can be applied directly on reconstructed images, thus eliminating the requirement for additional imaging data.

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Section: Resultsmentioning

confidence: 99%

“…Unfortunately, this technique induced new artifacts in the presence of wide and heavy rings. And a unidirectional relative total variation (URTV) model was also applied to polar coordinates to remove stripe artifacts …”

Section: Introductionmentioning

confidence: 99%

Removing ring artifacts in cone‐beam CT via TV‐Stokes and unidirectional total variation model

Wang

2019

Medical Physics

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“…Thus, different from the previous studies [19,21], we applied the ring-artifact correction on the projection domain. That is, our method is a pre-processing technique.…”

Section: B Other Advantages Of Our Methodsmentioning

confidence: 99%

“…On the other hand, the post-processing approaches operate in reconstructed images. Usually, they apply a polar-coordinate transformation and remove artifact components in the transformed images [18,19]. Although these methods are effective in ring-artifact removals, they lead to other problems such as blurring.…”

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confidence: 99%

Ring-Artifact Correction With Total-Variation Regularization for Material Images in Photon-Counting CT

Murata

Ogawa

2021

IEEE Trans. Radiat. Plasma Med. Sci.

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We propose a ring-artifact correction method with a compressed sensing for material images obtained with a photon-counting CT system. The ring-artifacts are caused by non-uniformity of detector properties. Conventional ring-artifact correction methods tend to degrade the quality of images. In contrast, compressed sensing methods can correct ring-artifacts with less degradation of the image quality owing to a priori knowledge that ring-artifacts appeared as stripes in sinograms. In this study, we extend the compressed sensing methods for material sinograms obtained with a photon-counting CT system. This is because material sinograms tend to be simpler and sparser, for which a compressed-sensing method can be more effective. We introduced a cost function with a TV-regularization term and positivity constraint, and optimized it with a prime-dual splitting method. The feasibility of this method was confirmed by simulations and an experiment. In both the simulations and experiment, the proposed method better corrected the ring artifacts than those on attenuation domain and without a priori knowledge. Comparison with previous methods in literature also showed the same results. These results suggest that our method is effective for correcting ring-artifacts in material images. Index Terms-image analysis, x-ray CT devices, photoncounting CT, ring artifacts, total variation, material decomposition. I. INTRODUCTION P HOTON-counting computed tomography (CT) is an emergence technology which measures X-ray intensity with multi-energy bands [1]. It provides many advantages compared with a conventional CT system. For example, it enables us to produce high-contrast images with appropriate energy weighting [2], to use multiple contrast-enhanced agents [3-6] and to perform a material-decomposition [7-11]. However, the material-decomposition is sensitive to quantum noise, uncertainty in sensitivity calibration, threshold variation, and other non-linear uncertainties such as pulse-pileup and charge-sharing effects. These uncertainties lead to ringartifacts in a reconstructed image [12]. Many methods of ring-artifact correction have been proposed. These can be classified into two categories: preprocessing and post-processing approaches [13,14]. The preprocessing approaches remove stripe-artifacts in sinograms before reconstructing images [15-17]. They can easily be combined with other projection-domain methods and any Manuscript

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“…Furthermore, a method that depends on TV-Stokes and unidirectional TV model was introduced to eliminate the ring artifact from cone-beam CT images [ 29 ]. Based on a unidirectional relative variation model, an approach was investigated to suppress the ring artifact [ 30 ]. Also, a variation-based method was formulated using ℓ 0 -norm/ ℓ 1 -norm regularization term to remove the ring artifact from the reconstructed images [ 4 ].…”

Section: Related Workmentioning

confidence: 99%

Sparsity-based method for ring artifact elimination in computed tomography

et al. 2022

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Ring artifact elimination is one of the popular problems in computed tomography (CT). It appears in the reconstructed image in the form of bright or dark patterns of concentric circles. In this paper, based on the compressed sensing theory, we propose a method for eliminating the ring artifact during the image reconstruction. The proposed method is based on representing the projection data by a sum of two components. The first component contains ideal correct values, while the latter contains imperfect error values causing the ring artifact. We propose to minimize some sparsity-induced norms corresponding to the imperfect error components to effectively eliminate the ring artifact. In particular, we investigate the effect of using different sparse models, i.e. different sparsity-induced norms, on the accuracy of the ring artifact correction. The proposed cost function is optimized using an iterative algorithm derived from the alternative direction method of multipliers. Moreover, we propose improved versions of the proposed algorithms by incorporating a smoothing penalty function into the cost function. We also introduce angular constrained forms of the proposed algorithms by considering a special case as follows. The imperfect error values are constant over all the projection angles, as in the case where the source of ring artifact is the non-uniform sensitivity of the detector. Real data and simulation studies were performed to evaluate the proposed algorithms. Results demonstrate that the proposed algorithms with incorporating smoothing penalty and their angular constrained forms are effective in ring artifact elimination.

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Removing ring artefacts in CT images via unidirectional relative variation model

Cited by 10 publications

References 9 publications

Removing ring artifacts in cone‐beam CT via TV‐Stokes and unidirectional total variation model

Removing ring artifacts in cone‐beam CT via TV‐Stokes and unidirectional total variation model

Ring-Artifact Correction With Total-Variation Regularization for Material Images in Photon-Counting CT

Sparsity-based method for ring artifact elimination in computed tomography

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