Reduction of streak artifacts caused by low photon counts utilizing an image-based forward projection in computed tomography

Niwa, Shin‐Ichi; Ichikawa, Katsuhiro; Kawashima, Hiroki; Takata, Takushi; Minami, S.; Mitsui, Wataru

doi:10.1016/j.compbiomed.2021.104583

Cited by 3 publications

(5 citation statements)

References 25 publications

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“…Therefore, it is necessary to point out that the most important artifacts present in real cardiac CT databases, synchronized by electrocardiographic signal, are those of type staircase and dark band [3,4]. The first artifact occurs when the electrocardiogram trigger is not correctly synchronized with the cardiac phase or when it overlaps the reconstructed sections.…”

Section: Discussionmentioning

confidence: 99%

Description and Use of Three-Dimensional Numerical Phantoms of Cardiac Computed Tomography Images

Vera

Bravo

Medina

2022

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The World Health Organization indicates the top cause of death is heart disease. These diseases can be detected using several imaging modalities, especially cardiac computed tomography (CT), whose images have imperfections associated with noise and certain artifacts. To minimize the impact of these imperfections on the quality of the CT images, several researchers have developed digital image processing techniques (DPIT) by which the quality is evaluated considering several metrics and databases (DB), both real and simulated. This article describes the processes that made it possible to generate and utilize six three-dimensional synthetic cardiac DBs or voxels-based numerical phantoms. An exhaustive analysis of the most relevant features of images of the left ventricle, belonging to a real CT DB of the human heart, was performed. These features are recreated in the synthetic DBs, generating a reference phantom or ground truth free of imperfections (DB1) and five phantoms, in which Poisson noise (DB2), stair-step artifact (DB3), streak artifact (DB4), both artifacts (DB5) and all imperfections (DB6) are incorporated. These DBs can be used to determine the performance of DPIT, aimed at decreasing the effect of these imperfections on the quality of cardiac images.

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Section: Discussionmentioning

confidence: 99%

Description and Use of Three-Dimensional Numerical Phantoms of Cardiac Computed Tomography Images

Vera

Bravo

Medina

2022

Data

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“…The processing technique used in forward projection was the same as that used in reducing streak artifacts by utilizing FP-data as reported by our laboratory team [ 3 ]. The report demonstrated that the CT images reconstructed from filtered FP-data had almost the same spatial resolution as that of the original images and had precisely the same CT numbers.…”

Section: Methodsmentioning

confidence: 99%

“…However, this potential has not been exploited widely so far. For example, to our best knowledge, only one paper reports its use in reducing the streak artifacts caused by low photon counts [ 3 ]. This limited use seems to be attributable to the large amount of computing time, and therefore cost, required for FP and the subsequent filter back projection (FBP) to reconstruct a CT image.…”

Section: Introductionmentioning

confidence: 99%

An image-based metal artifact reduction technique utilizing forward projection in computed tomography

Ichikawa,

Kawashima,

Takata

2024

Radiol Phys Technol

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The projection data generated via the forward projection of a computed tomography (CT) image (FP-data) have useful potentials in cases where only image data are available. However, there is a question of whether the FP-data generated from an image severely corrupted by metal artifacts can be used for the metal artifact reduction (MAR). The aim of this study was to investigate the feasibility of a MAR technique using FP-data by comparing its performance with that of a conventional robust MAR using projection data normalization (NMARconv). The NMARconv was modified to make use of FP-data (FPNMAR). A graphics processing unit was used to reduce the time required to generate FP-data and subsequent processes. The performances of FPNMAR and NMARconv were quantitatively compared using a normalized artifact index (AIn) for two cases each of hip prosthesis and dental fillings. Several clinical CT images with metal artifacts were processed by FPNMAR. The AIn values of FPNMAR and NMARconv were not significantly different from each other, showing almost the same performance between these two techniques. For all the clinical cases tested, FPNMAR significantly reduced the metal artifacts; thereby, the images of the soft tissues and bones obscured by the artifacts were notably recovered. The computation time per image was ~ 56 ms. FPNMAR, which can be applied to CT images without accessing the projection data, exhibited almost the same performance as that of NMARconv, while consuming significantly shorter processing time. This capability testifies the potential of FPNMAR for wider use in clinical settings.

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“…Based on the widely used equation for deriving CT numbers from attenuation data, each piece of data was transformed into a proportional function of its attenuation coefficient. The link between the numerical FP coordinates and the sampled data is depicted in Figure 3b, in which a projection data array is fixed and the position is interpolation [35]. In each ray position, the data sampling was repeated and accumulated at each projection angle 𝜃 as follows:

\begin{eqnarray} {P_\theta }(t) &=& \ln ({I_0}/I) = \int_{{l_{\theta ,t}}} {\mu \left( {x,y} \right)dl}\nonumber \\ &=& \int_{ - \infty }^\infty {\int_{ - \infty }^\infty {\mu \left( {x,y} \right)\delta (x\cos \theta + y\sin \theta - t)} } dxdy, \end{eqnarray}

…”

Section: Methodsmentioning

confidence: 99%

Section: Forward Projection Processing and Reconstructionmentioning

confidence: 99%

Complex artefact suppression for sparse reconstruction based on compensation approach in X‐ray computed tomography

Yang

Zhang

Huang

et al. 2022

IET Image Processing

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To provide high-quality imaging by decreasing the sparse view imaging artefact from the computed tomography (CT) images, this study addresses a new artefact suppression technique for sparse data for both single material and multi-material objects that have diverse materials. It begins with a pre-reconstructed image and a network of target patches that have been trained beforehand and then uses the forward projection (FP) approach to resolve the structural mutation brought on by sparse-view projection. As an edge-preserving operator to commit to the forward operator for sinogram correction, the bilateral filter was used. Both simulated and actual data have been gathered and evaluated in experiments. The suggested forward operator and normalized compensation (FONC) method produce results that have far smaller artefact and errors than those of more traditional techniques. For simulation # blade, the Normalized Mean Square Distance (NMSD) of the proposed method was reduced by 8.94%, Structural Similarity Index (SSIM) and the Universal Quality Index (UQI) were increased by 78.17% and 80.49%, respectively, which also demonstrate better uniformity of the results to practical data # pan, where the root mean squared error was reduced by 13.93%. SSIM and UQI were increased by 25.66% and 37.02%, respectively. The results conclusively show that the planned strategies are successful in eliminating artefact for irregular objects.

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Reduction of streak artifacts caused by low photon counts utilizing an image-based forward projection in computed tomography

Cited by 3 publications

References 25 publications

Description and Use of Three-Dimensional Numerical Phantoms of Cardiac Computed Tomography Images

Description and Use of Three-Dimensional Numerical Phantoms of Cardiac Computed Tomography Images

An image-based metal artifact reduction technique utilizing forward projection in computed tomography

Complex artefact suppression for sparse reconstruction based on compensation approach in X‐ray computed tomography

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