Spurious structures created by interpolation-based CT metal artifact reduction

Müller, J. Steffen; Buzug, Thorsten M.

doi:10.1117/12.813515

Cited by 50 publications

(71 citation statements)

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“…21,22 The principle behind the proposed method is to start with a first reconstruction of the acquired raw data and then subsequently improve the MAR. In a first step, metal artifacts are largely reduced by interpolating the metal traces in the raw data domain, followed by a second Feldkamp reconstruction.…”

Section: Mar Algorithmmentioning

confidence: 99%

Metal Artifact Reduction for Clipping and Coiling in Interventional C-Arm CT

Prell¹,

Kyriakou²,

Struffert³

et al. 2009

AJNR Am J Neuroradiol

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Section: Mar Algorithmmentioning

confidence: 99%

Metal Artifact Reduction for Clipping and Coiling in Interventional C-Arm CT

Prell¹,

Kyriakou²,

Struffert³

et al. 2009

AJNR Am J Neuroradiol

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“…not just metal object edges) lying on the beams passing through the metal objects is lost. Sinogram correction by this so-called 'naive interpolation' ultimately leads to the generation of secondary streaks in the corrected images [3,13]. Furthermore, in the presence of multiple metal objects, dark bands often appear between pairs of metal objects due to unequal quantities of beam hardening across views [14].…”

Section: Introductionmentioning

confidence: 99%

“…Muller and Buzug [13] have demonstrated that the biggest disadvantage of sinogram correction by direct interpolation is that all edge information (i.e. not just metal object edges) lying on the beams passing through the metal objects is lost.…”

Section: Introductionmentioning

confidence: 99%

“…This prior information allows for effective parameter tuning and can be used to 'guide' the interpolation process [3]. Those MAR techniques that rely on effective parameter tuning and/or prior information [13,18,19,20,21,22,23] are however, expected to be of limited value in the security screening domain, where the contents of the scans are inherently unpredictable making the generation of prior information and effective parameter tuning more challenging.…”

Section: Introductionmentioning

confidence: 99%

“…Pre-and post-filtering techniques [15,16], feedback strategies [17], guided sinogram completion techniques based on priors obtained via multiclass segmentation [13,18,19,20,21], wavelet techniques [22,23], Fourier-based interpolation [24] and region-specific interpolation [15,16] have been proposed and met with varying degrees of success. With the exception of [16], these methods are all intended for use in the medical field.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A distance driven method for metal artefact reduction in computed tomography

Mouton

Megherbi

Slambrouck

et al. 2013

2013 IEEE International Conference on Image Processing

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This paper presents an extension to a recent intensity-limiting sinogram completion-based Metal Artefact Reduction (MAR) algorithm for Computed Tomography (CT) images containing multiple metal objects. A novel weighting scheme is introduced, whereby the intensities of the MAR-corrected pixels are modified based on their spatial locations relative to the metal objects. Pixels falling within the straight-line regions connecting multiple metal objects are subjected to less intensive intensity-limiting, thereby compensating for the characteristic dark bands occurring in these regions. Extensive experimentation is performed on a state-of-the-art numerical simulation, a clinical CT data set and a baggage security CT data set. Comprehensive performance analysis, using reference and reference-free error metrics, Bland-Altman plots and visual comparisons, demonstrate an improvement in the restoration of the underestimated intensities occurring in the regions connecting multiple metal objects.

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Characterization of Metal Artifacts in X‐Ray Computed Tomography

Park

Choi

Seo

2017

Comm Pure Appl Math

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Metal streak artifacts in X‐ray computerized tomography (CT) are characterized here using the notion of the wavefront set from microlocal analysis. The metal artifacts are caused mainly from the mismatch of the forward model of the filtered back‐projection; the presence of metallic subjects in an imaging subject violates the model's assumption of the CT sinogram data being the Radon transform of an image. The increasing use of metallic implants has increased demand for the reduction of metal artifacts in the field of dental and medical radiography. However, it is a challenging issue due to the serious difficulties in analyzing the X‐ray data, which depends nonlinearly on the distribution of the metallic subject. In this paper, we, for the first time, provide a mathematical analysis to characterize the structure of metal streaking artifacts. The metal streaking artifacts are produced along the line tangent to boundaries of the metal region touching at least two different boundaries. We also found a sufficient condition for the nonexistence of the metal streaking artifacts. © 2017 Wiley Periodicals, Inc.

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Spurious structures created by interpolation-based CT metal artifact reduction

Cited by 50 publications

References 0 publications

Metal Artifact Reduction for Clipping and Coiling in Interventional C-Arm CT

Metal Artifact Reduction for Clipping and Coiling in Interventional C-Arm CT

A distance driven method for metal artefact reduction in computed tomography

Characterization of Metal Artifacts in X‐Ray Computed Tomography

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