Ring Artifacts Research Articles

Artifact reduction techniques in Cone Beam Computed Tomography (CBCT) imaging modality

Introduction: Cone beam computed tomography (CBCT) was introduced and became more common based on its low cost, fast image procedure rate and low radiation dose compared to CT. This imaging modality improved diagnostic and treatment-planning procedures by providing three-dimensional information with greatly reduced level of radiation dose compared to 2D dental imaging modalities for investigation of maxillofacial skeleton, dentition and the relationship of anatomical structures. However, CBCT is associated with multiple artifacts like. Extinction artifacts, beam hardening artifacts, partial volume effect, aliasing artifacts, ring artifacts and motion artifacts (misalignment artifacts), Noise and scatter. All of them leads to image quality reduction and have capability of Mistakenly considering as a pathological lesion. This study aimed to investigate Cone Beam Computed Tomography artifacts and their reduction procedures. Materials and Methods: A systematic search of the literature published from 2000 to 2017 in the PubMed, scopus and web of science databases was performed. The following key words combined in different ways: cone beam computed tomography, CBCT Artifacts and artifact reduction. Results: Artifact is caused by several factors containing reconstruction parameters like small field of views (FOVs), presence of metal objects, patient movement, etc. Artifact reduction methods can have divided into two categorize preprocessing in the projection domain and post processing in the image domain. Limitation of field of view, modification of patient head position or separating dental arches for scatter reduction, Application of high KVP in order to beam hardening reduction, iterative method and projection modification method for metal artifacts are recommended. In addition, Filtration, interpolation, iterative reconstruction and filtering algorithms, application of the smaller voxel size and respiratory gating are other suggested items for artifact reduction in CBCT. Conclusion: Multiple artifacts accompany CBCT imaging procedures. There for With the aim of improving the quality of the CBCT images; reducing the artifact caused scatter photons , various software-based and hardware-based correction methods are recommended .

Superior techniques for eliminating ring artifacts in X-ray micro-tomography.

Synchrotron-based X-ray micro-tomography systems often suffer severe ring artifacts in reconstructed images. In sinograms the artifacts appear as straight lines or stripe artifacts. These artifacts are caused by the irregular response of a detecting system giving rise to a variety of observed types of stripes: full stripes, partial stripes, fluctuating stripes, and unresponsive stripes. The use of pre-processing techniques such as distortion correction or phase retrieval blurs and enlarges these stripes. It is impossible for a single approach to remove all types of stripe artifacts. Here, we propose three techniques for tackling all of them. The proposed techniques are easy to implement; do not generate extra stripe artifacts and void-center artifacts; and give superior quality on challenging data sets and in comparison with other techniques. Implementations in Python and a challenging data set are available for download.

The impact of secondary fragments on the image quality of helium ion imaging

Single-event ion imaging enables the direct reconstruction of the relative stopping power (RSP) information required for ion-beam therapy. Helium ions were recently hypothesized to be the optimal species for such technique. The purpose of this work is to investigate the effect of secondary fragments on the image quality of helium CT (HeCT) and to assess the performance of a prototype proton CT (pCT) scanner when operated with helium beams in Monte Carlo simulations and experiment.Experiments were conducted installing the U.S. pCT consortium prototype scanner at the Heidelberg Ion-Beam Therapy Center (HIT). Simulations were performed with the scanner using the TOPAS toolkit. HeCT images were reconstructed for a cylindrical water phantom, the CTP404 (sensitometry), and the CTP528 (line-pair) ® modules. To identify and remove individual events caused by fragmentation, the multistage energy detector of the scanner was adapted to function as a telescope.The use of the developed filter eliminated the otherwise arising ring artifacts in the HeCT reconstructed images. For the HeCT reconstructed images of a water phantom, the maximum RSP error was improved by almost a factor 8 with respect to unfiltered images in the simulation and a factor 10 in the experiment. Similarly, for the CTP404 module, the mean RSP accuracy improved by a factor 6 in both the simulation and the experiment when the filter was applied (mean relative error 0.40% in simulation, 0.45% in experiment). In the evaluation of the spatial resolution through the CTP528 module, the main effect of the filter was noise reduction. For both simulated and experimental images the spatial resolution was ∼4 lp cm−1.In conclusion, the novel filter developed for secondary fragments proved to be effective in improving the visual quality and RSP accuracy of the reconstructed images. With the filter, the pCT scanner is capable of accurate HeCT imaging.

Dynamic Volume Lines: Visual Comparison of 3D Volumes through Space-filling Curves.

The comparison of many members of an ensemble is difficult, tedious, and error-prone, which is aggravated by often just subtle differences. In this paper, we introduce Dynamic Volume Lines for the interactive visual analysis and comparison of sets of 3D volumes. Each volume is linearized along a Hilbert space-filling curve into a 1D Hilbert line plot, which depicts the intensities over the Hilbert indices. We present a nonlinear scaling of these 1D Hilbert line plots based on the intensity variations in the ensemble of 3D volumes, which enables a more effective use of the available screen space. The nonlinear scaling builds the basis for our interactive visualization techniques. An interactive histogram heatmap of the intensity frequencies serves as overview visualization. When zooming in, the frequencies are replaced by detailed 1D Hilbert line plots and optional functional boxplots. To focus on important regions of the volume ensemble, nonlinear scaling is incorporated into the plots. An interactive scaling widget depicts the local ensemble variations. Our brushing and linking interface reveals, for example, regions with a high ensemble variation by showing the affected voxels in a 3D spatial view. We show the applicability of our concepts using two case studies on ensembles of 3D volumes resulting from tomographic reconstruction. In the first case study, we evaluate an artificial specimen from simulated industrial 3D X-ray computed tomography (XCT). In the second case study, a real-world XCT foam specimen is investigated. Our results show that Dynamic Volume Lines can identify regions with high local intensity variations, allowing the user to draw conclusions, for example, about the choice of reconstruction parameters. Furthermore, it is possible to detect ring artifacts in reconstructions volumes.

Removal of Ring Artifacts in Microtomography by Characterization of Scintillator Variations - an Extension to Phase Contrast

Removal of Ring Artifacts in Microtomography by Characterization of Scintillator Variations - an Extension to Phase Contrast

P016] Performance of 3 CT scanners: Results from a 4 year period

Purpose Present the results of a 4 years period quality control routine test performed on 3 CT scanners (Siemens Somaton Sensation Open (S), Toshiba Aquilion 16 (T) and Ge HiSpeed Lx/i (G)) to assure compliance of the monitored parameters with baseline values and detect system performance malfunctioning. The weekly test, is a 15 minute check acquisition of the CATPHAN 600 phantom sections. Methods Baseline values were established using the average of 10 images in sequential mode 120 kV, 200 mAs(T), 280 mAs(S) and 300 mAs(G), collimation 1 × 5 mm(SG 31 mGy(G); 35 mGy(S). Performance indicators: Noise Index (standard deviation of the HU measured in a central ROI of 28 cm[b] (40% useful radius) Homogeneity index (maximum difference on the average HU measured in 4 periphery ROI’s relative to a central ROI each with 10cm2); Spatial Resolution Index (zoomed visualization of the last perceptible group of a lp/cm pattern using constant WW, WL); Low Contrast Index (CD – diameter * percentage contrast (mm*%) for each target – 3 groups of different sized low contrast targets 10HU, 5HU, 3HU – 2 images averaged; HU index (average HU in 45 mm[b] ROI’s of 8 target materials from −1000 up to 1000 HU. Results Noise index: σ(T) = 5.36 ± 2%; σ(G) = 2.87 ± 3%; σ(T) = 4.01 ± 5%; maximum deviations: 8.6%(T); 3.1%(G); 4.7%(S); outliers(>10%): two (12.3;16.0%(T)); one 21.6%(G); zero(S). Homogeneity index: HU = 9.53 ± 4%(T); HU = 7.1 ± 3%(G); HU = 12.7 ± 3%(S); maximum difference deviations: 14.7%(T); 14.5%(G); 12.6%(S); outliers(>15%): six(16.7;15.7%(T)) one 24.2%(G); zero(S). Spatial Resolution index (lp/cm): 9(T); 7(G); 8(S); CD index (mm*%): Conclusions The customized test proved to be a simplified but incomplete method for system performance consistency evaluation since it was inefficient in the detection of ring artifacts caused by faults in detector system calibration for the head protocol. The addition of a spiral acquisition in the homogenous section, lead to direct visualization and awareness of this type of artifacts but still do not prevent the detection of artifacts in larger FOVs or in special collimation sets depending on the CT scanner design.

An Innovative Practical Automatic Segmentation of Ultrasound Computer Tomography Images Acquired from USCT System

A 3D ultrasound computer tomography (USCT) device with a nearly isotropic and spatially invariant 3D point spread function has been constructed at Institute for Data Processing and Electronic (IPE), Karlsruhe Institute of Technology (KIT). This device is currently applied in clinical studies for breast cancer screening. In this paper, a new method to develop an automated segmentation algorithm for USCT acquired images is proposed. The method employs distance regularized level set evolutionary (DRLSE) active contours along with surface fitting extrapolation and 3D binary mask generation for fully automatic segmentation outcome. In the first stage of the proposed algorithm, DRLSE is applied to those 3D USCT slice images which contain breast and are less affected by noise and ring artifacts named as Cat2. The DRLSE segmentation results are employed to extrapolate the rest of slice images known as Cat1. To overcome defectively segmented slice images, a 3D binary mask is generated out of USCT attenuation images. The 3D binary mask is multiplied by the DRLSE-based segmentation results to form finally segmented 3D USCT images. The method was tested on 12 clinical dataset images. According to F-measure criterion, the proposed method shows higher performance than the previously proposed semiautomatic segmentation one.

Application of fractal dimension for quantifying noise texture in computed tomography images.

Evaluation of noise texture information in CT images is important for assessing image quality. Noise texture is often quantified by the noise power spectrum (NPS), which requires numerous image realizations to estimate. This study evaluated fractal dimension for quantifying noise texture as a scalar metric that can potentially be estimated using one image realization. The American College of Radiology CT accreditation phantom (ACR) was scanned on a clinical scanner (Discovery CT750, GE Healthcare) at 120kV and 25 and 90mAs. Images were reconstructed using filtered back projection (FBP/ASIR 0%) with varying reconstruction kernels: Soft, Standard, Detail, Chest, Lung, Bone, and Edge. For each kernel, images were also reconstructed using ASIR 50% and ASIR 100% iterative reconstruction (IR) methods. Fractal dimension was estimated using the differential box-counting algorithm applied to images of the uniform section of ACR phantom. The two-dimensional Noise Power Spectrum (NPS) and one-dimensional-radially averaged NPS were estimated using established techniques. By changing the radiation dose, the effect of noise magnitude on fractal dimension was evaluated. The Spearman correlation between the fractal dimension and the frequency of the NPS peak was calculated. The number of images required to reliably estimate fractal dimension was determined and compared to the number of images required to estimate the NPS-peak frequency. The effect of Region of Interest (ROI) size on fractal dimension estimation was evaluated. Feasibility of estimating fractal dimension in an anthropomorphic phantom and clinical image was also investigated, with the resulting fractal dimension compared to that estimated within the uniform section of the ACR phantom. Fractal dimension was strongly correlated with the frequency of the peak of the radially averaged NPS curve, having a Spearman rank-order coefficient of 0.98 (P-value<0.01) for ASIR 0%. The mean fractal dimension at ASIR 0% was 2.49 (Soft), 2.51 (Standard), 2.52 (Detail), 2.57 (Chest), 2.61 (Lung), 2.66 (Bone), and 2.7 (Edge). A reduction in fractal dimension was observed with increasing ASIR levels for all investigated reconstruction kernels. Fractal dimension was found to be independent of noise magnitude. Fractal dimension was successfully estimated from four ROIs of size 64×64 pixels or one ROI of 128×128 pixels. Fractal dimension was found to be sensitive to non-noise structures in the image, such as ring artifacts and anatomical structure. Fractal dimension estimated within a uniform region of an anthropomorphic phantom and clinical head image matched that estimated within the ACR phantom for filtered back projection reconstruction. Fractal dimension correlated with the NPS-peak frequency and was independent of noise magnitude, suggesting that the scalar metric of fractal dimension can be used to quantify the change in noise texture across reconstruction approaches. Results demonstrated that fractal dimension can be estimated from four, 64×64-pixel ROIs or one 128×128 ROI within a head CT image, which may make it amenable for quantifying noise texture within clinical images.

Squdel Function: Square Wave Approximation Without Ringing

A function that is well suited to describe a square wave as well as a sequence of delta functions is presented. The squdel function has a closed rational form instead of a series approximation. Bandwidth limitations are readily incorporated in this function without producing undesirable ringing artifacts. The squdel function is infinitely differentiable and analytic for a squareness parameter as close as required to the square function provided that the limit is not taken. Even its Fourier series decomposition does not exhibit overshooting when truncated. Two-dimensional soft pixel structures are shown to be economically modeled with this function.

Curvelet‐based multiscale denoising using non‐local means &amp; guided image filter

This study presents an image denoising technique using multiscale non-local means (NLM) filtering combined with hard thresholding in curvelet domain. The inevitable ringing artefacts in the reconstructed image - due to thresholding - is further processed using a guided image filter for better preservation of local structures like edges, textures and small details. The authors decomposed the image into three different curvelet scales including the approximation and the fine scale. The low-frequency noise in the approximation sub-band and the edges with small textural details in the fine scale are processed independently using a multiscale NLM filter. On the other hand, the hard thresholding in the remaining coarser scale is applied to separate the signal and the noise subspace. Experimental results on both greyscale and colour images indicate that the proposed approach is competitive at lower noise strength with respect to peak signal to noise ratio and structural similarity index measure and excels in performance at higher noise strength compared with several state-of-the-art algorithms.

A Practical Computed Tomography Image Ring Artifact Correction Method for Large-Scale Dead Pixels of X-ray Detector

A Practical Computed Tomography Image Ring Artifact Correction Method for Large-Scale Dead Pixels of X-ray Detector

Efficient correction of wavefront inhomogeneities in X-ray holographic nanotomography by random sample displacement

In X-ray tomography, ring-shaped artifacts present in the reconstructed slices are an inherent problem degrading the global image quality and hindering the extraction of quantitative information. To overcome this issue, we propose a strategy for suppression of ring artifacts originating from the coherent mixing of the incident wave and the object. We discuss the limits of validity of the empty beam correction in the framework of a simple formalism. We then deduce a correction method based on two-dimensional random sample displacement, with minimal cost in terms of spatial resolution, acquisition, and processing time. The method is demonstrated on bone tissue and on a hydrogen electrode of a ceramic-metallic solid oxide cell. Compared to the standard empty beam correction, we obtain high quality nanotomography images revealing detailed object features. The resulting absence of artifacts allows straightforward segmentation and posterior quantification of the data.

Use of a CMOS-based micro-CT system to validate a ring artifact correction algorithm on low-dose image data.

The imaging of objects using high-resolution detectors coupled to CT systems may be made challenging due to the presence of ring artifacts in the reconstructed data. Not only are the artifacts qualitatilvely distracting, they reduce the SNR of the reconstructed data and may lead to a reduction in the clinical utility of the image data. To address these challenges, we introduce a multistep algorithm that greatly reduces the impact of the ring artifacts on the reconstructed data through image processing in the sinogram space. First, for a single row of detectors corresponding to one slice, we compute the mean of every detector element in the row across all projection view angles and place the reciprocal values in a vector with length equal to the number of detector elements in a row. This vector is then multiplied with each detector element value for each projection view angle, obtaining a normalized or corrected sinogram. This sinogram is subtracted from the original uncorrected sinogram of the slice to obtain a difference map, which is then blurred with a median filter along the row direction. This blurred difference map is summed back to the corrected sinogram, to obtain the final sinogram, which can be back projected to obtain an axial slice of the scanned object, with a greatly reduced presence of ring artifacts. This process is done for each detector row corresponding to each slice. The performance of this algorithm was assessed using images of a mouse femur. These images were acquired using a micro-CT system coupled to a high-resolution CMOS detector. We found that the use of this algorithm led to an increase in SNR and a more uniform line-profile, as a result of the reduction in the presence of the ring artifacts.

Combine TV-L1 model with guided image filtering for wide and faint ring artifacts correction of in-line x-ray phase contrast computed tomography.

In practice, mis-calibrated detector pixels give rise to wide and faint ring artifacts in the reconstruction image of the In-line phase-contrast computed tomography (IL-PC-CT). Ring artifacts correction is essential in IL-PC-CT. In this study, a novel method of wide and faint ring artifacts correction was presented based on combining TV-L1 model with guided image filtering (GIF) in the reconstruction image domain. The new correction method includes two main steps namely, the GIF step and the TV-L1 step. To validate the performance of this method, simulation data and real experimental synchrotron data are provided. The results demonstrate that TV-L1 model with GIF step can effectively correct the wide and faint ring artifacts for IL-PC-CT.

Ring artifact reduction in synchrotron x-ray tomography through helical acquisition

In synchrotron x-ray tomography, systematic defects in certain detector elements can result in arc-shaped artifacts in the final reconstructed image of the scanned sample. These ring artifacts are commonly found in many applications of synchrotron tomography, and can make it difficult or impossible to use the reconstructed image in further analyses. The severity of ring artifacts is often reduced in practice by applying pre-processing on the acquired data, or post-processing on the reconstructed image. However, such additional processing steps can introduce additional artifacts as well, and rely on specific choices of hyperparameter values.In this paper, a different approach to reducing the severity of ring artifacts is introduced: a helical acquisition mode. By moving the sample parallel to the rotation axis during the experiment, the sample is detected at different detector positions in each projection, reducing the effect of systematic errors in detector elements. Alternatively, helical acquisition can be viewed as a way to transform ring artifacts to helix-like artifacts in the reconstructed volume, reducing their severity. We show that data acquired with the proposed mode can be transformed to data acquired with a virtual circular trajectory, enabling further processing of the data with existing software packages for circular data. Results for both simulated data and experimental data show that the proposed method is able to significantly reduce ring artifacts in practice, even compared with popular existing methods, without introducing additional artifacts.

An improved ring removal procedure for in-line x-ray phase contrast tomography

The suppression of ring artifacts in x-ray computed tomography (CT) is a required step in practical applications; it can be addressed by introducing refined digital low pass filters within the reconstruction process. However, these filters may introduce additional ringing artifacts when simultaneously imaging pure phase objects and elements having a non-negligible absorption coefficient. Ringing originates at sharp interfaces, due to the truncation of spatial high frequencies, and severely affects qualitative and quantitative analysis of the reconstructed slices. In this work, we discuss the causes of ringing artifacts, and present a general compensation procedure to account for it. The proposed procedure has been tested with CT datasets of the mouse central nervous system acquired at different synchrotron radiation facilities. The results demonstrate that the proposed method compensates for ringing artifacts induced by low pass ring removal filters. The effectiveness of the ring suppression filters is not altered; the proposed method can thus be considered as a framework to improve the ring removal step, regardless of the specific filter adopted or the imaged sample.

Regularized iterative Weiner filter method for blind image deconvolution

Abstract Blind image deconvolution is a highly ill-posed problem. As a generalization of the well known Weiner filter, the existing iterative Weiner filter (IWF) method for blind image deconvolution is unstable and suffers from serious ringing artifacts. To overcome these drawbacks, in this paper, we propose two novel regularized iterative Weiner filter methods. We assume that both the latent image and the convolution kernel can be estimated by applying two different filters on the observed image. To estimate the filters, we propose to minimize energy functionals combined by the mean square errors with some regularization terms. Both H 1 and total variation (TV) regularization are considered. By applying alternating minimization method and operator splitting technique, we derive iterative algorithms for each regularization method. The proposed methods are effective for blind deconvolution of Gaussian blurred images which is widely observed in real applications such as microscopic images. Numerical experimental results on both synthetic images and real microscopic images are presented. The comparisons show that the proposed regularized algorithms perform better than the closely related state-of-the-art methods in terms of peak signal-to-noise ratio (PSNR) and visual quality.

Inpainting approaches to fill in detector gaps in phase contrast computed tomography

Photon counting semiconductor detectors in radiation imaging present attractive properties, such as high efficiency, low noise, and energy sensitivity. The very complex electronics limits the sensitive area of current devices to a few square cm. This disadvantage is often compensated by tiling a larger matrix with an adequate number of detector units but this usually results in non-negligible insensitive gaps between two adjacent modules. When considering the case of Computed Tomography (CT), these gaps lead to degraded reconstructed images with severe streak and ring artifacts. This work presents two digital image processing solutions to fill in these gaps when considering the specific case of synchrotron radiation x-ray parallel beam phase contrast CT. While not discussed with experimental data, other CT modalities, such as spectral, cone beam and other geometries might benefit from the presented approaches.

21. Assessing image quality of kilo-voltage cone beam CT (kV-CBCT) for adaptive radiotherapy

Introduction The scope of this study was to review and compare quality of kV-CBCT imaging highlighted from different generation systems and their respective main issues in regards with fan-beam CT (FBCT). Indeed kV-CBCT beam geometry is different from FBCT, introducing much more artefacts and leading to inaccuracies to convert Hounsfield Units (HU) into the relative electron density. This should be explored in depth because kV-CBCT is potentially the reference data for new approaches such computation of the daily actual delivered dose. Methods Different kV-CBCT acquisition modes with various tube voltage (kV) and exposure (mAs) were studied: “pelvis” and “pelvis obese” with a Varian Truebeam™ (unit 1), “pelvis” and “low dose thorax” with a Varian Clinac 2100CD (unit 2). Using the TomoTherapy® Cheese phantom (Gammex RMI, Middleton, WI) for HU to electron density (de) calibration curve, and the NEMA body water phantom for HU uniformity, noise and mean water number analysis, were investigated. From the FBCT and kV-CBCT HU differential histograms, frequency peaks representing water, air, lung, soft tissue and bone were compared. Results For unit 2, streaking and ring artifacts are much greater than for unit 1 as well as HU uniformity is deteriorated. Noise values are comparable between units but standard deviation is twice at unit 2. Peaks observed in the differential histograms are broader in kV-CBCT than those of FBCT especially for high tissue density. kV-CBCT uniformity is more degraded than in FBCT because CBCT is more prone to artefacts in images such as: streaking, cupping, or ring artifacts. Variations in calibration protocols were observed between FBCT and kV-CBCT that could explain differences for mean water number. Conclusions The two commercial kV-CBCT systems demonstrate different performances. We found that HU differential histograms are an efficient way for comparing and controlling image quality in addition to existing quality metrics.

Detector-unit-dependent calibration for polychromatic projections of rock core CT.

Computed tomography (CT) plays an important role in digital rock analysis, which is a new prospective technique for oil and gas industry. But the artifacts in CT images will influence the accuracy of the digital rock model. In this study, we proposed and demonstrated a novel method to restore detector-unit-dependent functions for polychromatic projection calibration by scanning some simple shaped reference samples. As long as the attenuation coefficients of the reference samples are similar to the scanned object, the size or position is not needed to be exactly known. Both simulated and real data were used to verify the proposed method. The results showed that the new method reduced both beam hardening artifacts and ring artifacts effectively. Moreover, the method appeared to be quite robust.