Suppression of metal artifacts in CT using a reconstruction procedure that combines MAP and projection completion

An Image-Based Reduction of Metal Artifacts in Computed Tomography

OBJECTIVE

Various strategies have been developed in the past to reduce the excessive effects of metal artifacts in computed tomography images. From straightforward sinogram inpainting-based methods to computationally expensive iterative methods, all have been successful in improving the image quality up to a certain degree. We propose a novel image-based metal artifact subtraction method that achieves a superior image quality and at the same time provides a quantitatively more accurate image.

METHODS

Our proposed method consists of prior image-based sinogram inpainting, metal sinogram extraction, and metal artifact image subtraction. Reconstructing the metal images from the extracted metal-contaminated portions in the sinogram yields a streaky image that eventually can be subtracted from the uncorrected image. The prior image is reconstructed from the sinogram that is free from the metal-contaminated portions by use of a total variation (TV) minimization algorithm, and the reconstructed prior image is fed into the forward projector so that the missing portions in the sinogram can be recovered. Image quality of the metal artifact-reduced images on selected areas was assessed by the structure similarity index for the simulated data and SD for the real dental data.

RESULTS

Simulation phantom studies showed higher structure similarity index values for the proposed metal artifact reduction (MAR) images than the standard MAR images. Thus, more artifact suppression was observed in proposed MAR images. In real dental phantom data study, lower SD values were calculated from the proposed MAR images. The findings in real human arm study were also consistent with the results in all phantom studies. Thus, compared with standard MAR images, lesser artifact intensity was exhibited by the proposed MAR images.

CONCLUSIONS

From the quantitative calculations, our proposed method has shown to be effective and superior to the conventional approach in both simulation and real dental phantom cases.

Learning-Based Object Identification and Segmentation Using Dual-Energy CT Images for Security

In recent years, baggage screening at airports has included the use of dual-energy X-ray computed tomography (DECT), an advanced technology for nondestructive evaluation. The main challenge remains to reliably find and identify threat objects in the bag from DECT data. This task is particularly hard due to the wide variety of objects, the high clutter, and the presence of metal, which causes streaks and shading in the scanner images. Image noise and artifacts are generally much more severe than in medical CT and can lead to splitting of objects and inaccurate object labeling. The conventional approach performs object segmentation and material identification in two decoupled processes. Dual-energy information is typically not used for the segmentation, and object localization is not explicitly used to stabilize the material parameter estimates. We propose a novel learning-based framework for joint segmentation and identification of objects directly from volumetric DECT images, which is robust to streaks, noise and variability due to clutter. We focus on segmenting and identifying a small set of objects of interest with characteristics that are learned from training images, and consider everything else as background. We include data weighting to mitigate metal artifacts and incorporate an object boundary field to reduce object splitting. The overall formulation is posed as a multilabel discrete optimization problem and solved using an efficient graph-cut algorithm. We test the method on real data and show its potential for producing accurate labels of the objects of interest without splits in the presence of metal and clutter.

Dosimetric impact of orthopedic metal artifact reduction (O-MAR) on Spine SBRT patients

The dosimetric impact of orthopedic metal artifact reduction (O‐MAR) on spine SBRT patients has not been comprehensively studied, particularly with spinal prostheses in high‐dose gradient regions. Using both phantom and patient datasets, we investigated dosimetric effects of O‐MAR in combination of various metal locations and dose calculation algorithms. A physical phantom, with and without a titanium insert, was scanned. A clinical patient plan was applied to the artifact‐free reference, non‐O‐MAR, and O‐MAR phantom images with the titanium located either inside or outside of the tumor. Subsequently, five clinical patient plans were calculated with pencil beam and Monte Carlo (iPlan) on non‐O‐MAR and O‐MAR patient images using an extended CT‐density table. The dose differences for phantom plans and patient plans were analyzed using dose distributions, dose‐volume histograms (DVHs), gamma index, and selected dosimetric endpoints. From both phantom plans and patient plans, O‐MAR did not affect dose distributions and DVHs while minimizing metal artifacts. Among patient plans, we found that, when the same dose calculation method was used, the difference in the dosimetric endpoints between non‐O‐MAR and O‐MAR datasets were small. In conclusion, for spine SBRT patients with spinal prostheses, O‐MAR image reconstruction does not affect dose calculation accuracy while minimizing metal artifacts. Therefore, O‐MAR images can be safely used for clinical spine SBRT treatment planning.

PACS numbers: 87.53.Bn, 87.55.K‐, 87.57.Q‐, 87.57.cp

Value of monoenergetic dual-energy CT (DECT) for artefact reduction from metallic orthopedic implants in post-mortem studies

OBJECTIVES

The aim of this ex vivo study was to assess the performance of monoenergetic dual-energy CT (DECT) reconstructions to reduce metal artefacts in bodies with orthopedic devices in comparison with standard single-energy CT (SECT) examinations in forensic imaging. Forensic and clinical impacts of this study are also discussed.

MATERIALS AND METHODS

Thirty metallic implants in 20 consecutive cadavers with metallic implants underwent both SECT and DECT with a clinically suitable scanning protocol. Extrapolated monoenergetic DECT images at 64, 69, 88, 105, 120, and 130 keV and individually adjusted monoenergy for optimized image quality (OPTkeV) were generated. Image quality of the seven monoenergetic images and of the corresponding SECT image was assessed qualitatively and quantitatively by visual rating and measurements of attenuation changes induced by streak artefact.

RESULTS

Qualitative and quantitative analyses showed statistically significant differences between monoenergetic DECT extrapolated images and SECT, with improvements in diagnostic assessment in monoenergetic DECT at higher monoenergies. The mean value of OPTkeV was 137.6 ± 4.9 with a range of 130 to 148 keV.

CONCLUSIONS

This study demonstrates that monoenergetic DECT images extrapolated at high energy levels significantly reduce metallic artefacts from orthopedic implants and improve image quality compared to SECT examination in forensic imaging.

Reduction of metallic coil artefacts in computed tomography body imaging: effects of a new single-energy metal artefact reduction algorithm

OBJECTIVES

We evaluated the effect of a single-energy metal artefact reduction (SEMAR) algorithm for metallic coil artefact reduction in body imaging.

METHODS

Computed tomography angiography (CTA) was performed in 30 patients with metallic coils (10 men, 20 women; mean age, 67.9 ± 11 years). Non-SEMAR images were reconstructed with iterative reconstruction alone, and SEMAR images were reconstructed with the iterative reconstruction plus SEMAR algorithms. We compared image noise around metallic coils and the maximum diameters of artefacts from coils between the non-SEMAR and SEMAR images. Two radiologists visually evaluated the metallic coil artefacts utilizing a four-point scale: 1 = extensive; 2 = strong; 3 = mild; 4 = minimal artefacts.

RESULTS

The image noise and maximum diameters of the artefacts of the SEMAR images were significantly lower than those of the non-SEMAR images (65.1 ± 33.0 HU vs. 29.7 ± 10.3 HU; 163.9 ± 54.8 mm vs. 10.3 ± 19.0 mm, respectively; P < 0.001). Better visual scores were obtained with the SEMAR technique (3.4 ± 0.6 vs. 1.0 ± 0.0, P < 0.001).

CONCLUSIONS

The SEMAR algorithm significantly reduced artefacts caused by metallic coils compared with the non-SEMAR algorithm. This technique can potentially increase CT performance for the evaluation of post-coil embolization complications.

KEY POINTS

• The new algorithm involves a raw data- and image-based reconstruction technique. • The new algorithm mitigates artefacts from metallic coils on body CT images. • The new algorithm significantly reduced artefacts caused by metallic coils. • The metal artefact reduction algorithm improves CT image quality after coil embolization.

Statistical iterative reconstruction algorithm for X-ray phase-contrast CT

Grating-based phase-contrast computed tomography (PCCT) is a promising imaging tool on the horizon for pre-clinical and clinical applications. Until now PCCT has been plagued by strong artifacts when dense materials like bones are present. In this paper, we present a new statistical iterative reconstruction algorithm which overcomes this limitation. It makes use of the fact that an X-ray interferometer provides a conventional absorption as well as a dark-field signal in addition to the phase-contrast signal. The method is based on a statistical iterative reconstruction algorithm utilizing maximum-a-posteriori principles and integrating the statistical properties of the raw data as well as information of dense objects gained from the absorption signal. Reconstruction of a pre-clinical mouse scan illustrates that artifacts caused by bones are significantly reduced and image quality is improved when employing our approach. Especially small structures, which are usually lost because of streaks, are recovered in our results. In comparison with the current state-of-the-art algorithms our approach provides significantly improved image quality with respect to quantitative and qualitative results. In summary, we expect that our new statistical iterative reconstruction method to increase the general usability of PCCT imaging for medical diagnosis apart from applications focused solely on soft tissue visualization.

Evaluation of a prototype correction algorithm to reduce metal artefacts in flat detector computed tomography of scaphoid fixation screws

OBJECTIVES

The aim of this study was to evaluate a prototype correction algorithm to reduce metal artefacts in flat detector computed tomography (FDCT) of scaphoid fixation screws. FDCT has gained interest in imaging small anatomic structures of the appendicular skeleton. Angiographic C-arm systems with flat detectors allow fluoroscopy and FDCT imaging in a one-stop procedure emphasizing their role as an ideal intraoperative imaging tool. However, FDCT imaging can be significantly impaired by artefacts induced by fixation screws.

MATERIALS AND METHODS

Following ethical board approval, commercially available scaphoid fixation screws were inserted into six cadaveric specimens in order to fix artificially induced scaphoid fractures. FDCT images corrected with the algorithm were compared to uncorrected images both quantitatively and qualitatively by two independent radiologists in terms of artefacts, screw contour, fracture line visibility, bone visibility, and soft tissue definition. Normal distribution of variables was evaluated using the Kolmogorov-Smirnov test. In case of normal distribution, quantitative variables were compared using paired Student's t tests. The Wilcoxon signed-rank test was used for quantitative variables without normal distribution and all qualitative variables. A p value of < 0.05 was considered to indicate statistically significant differences.

RESULTS

Metal artefacts were significantly reduced by the correction algorithm (p < 0.001), and the fracture line was more clearly defined (p < 0.01). The inter-observer reliability was "almost perfect" (intra-class correlation coefficient 0.85, p < 0.001).

CONCLUSIONS

The prototype correction algorithm in FDCT for metal artefacts induced by scaphoid fixation screws may facilitate intra- and postoperative follow-up imaging.

KEY POINTS

Flat detector computed tomography (FDCT) is a helpful imaging tool for scaphoid fixation. The correction algorithm significantly reduces artefacts in FDCT induced by scaphoid fixation screws. This may facilitate intra- and postoperative follow-up imaging.

Metal artifact correction for x-ray computed tomography using kV and selective MV imaging

PURPOSE

The overall goal of this work is to improve the computed tomography (CT) image quality for patients with metal implants or fillings by completing the missing kilovoltage (kV) projection data with selectively acquired megavoltage (MV) data that do not suffer from photon starvation. When both of these imaging systems, which are available on current radiotherapy devices, are used, metal streak artifacts are avoided, and the soft-tissue contrast is restored, even for regions in which the kV data cannot contribute any information.

METHODS

Three image-reconstruction methods, including two filtered back-projection (FBP)-based analytic methods and one iterative method, for combining kV and MV projection data from the two on-board imaging systems of a radiotherapy device are presented in this work. The analytic reconstruction methods modify the MV data based on the information in the projection or image domains and then patch the data onto the kV projections for a FBP reconstruction. In the iterative reconstruction, the authors used dual-energy (DE) penalized weighted least-squares (PWLS) methods to simultaneously combine the kV/MV data and perform the reconstruction.

RESULTS

The authors compared kV/MV reconstructions to kV-only reconstructions using a dental phantom with fillings and a hip-implant numerical phantom. Simulation results indicated that dual-energy sinogram patch FBP and the modified dual-energy PWLS method can successfully suppress metal streak artifacts and restore information lost due to photon starvation in the kV projections. The root-mean-square errors of soft-tissue patterns obtained using combined kV/MV data are 10-15 Hounsfield units smaller than those of the kV-only images, and the structural similarity index measure also indicates a 5%-10% improvement in the image quality. The added dose from the MV scan is much less than the dose from the kV scan if a high efficiency MV detector is assumed.

CONCLUSIONS

The authors have shown that it is possible to improve the image quality of kV CTs for patients with metal implants or fillings by completing the missing kV projection data with selectively acquired MV data that do not suffer from photon starvation. Numerical simulations demonstrated that dual-energy sinogram patch FBP and a modified kV/MV PWLS method can successfully suppress metal streak artifacts and restore information lost due to photon starvation in kV projections. Combined kV/MV images may permit the improved delineation of structures of interest in CT images for patients with metal implants or fillings.

Prior-based artifact correction (PBAC) in computed tomography

PURPOSE

Image quality in computed tomography (CT) often suffers from artifacts which may reduce the diagnostic value of the image. In many cases, these artifacts result from missing or corrupt regions in the projection data, e.g., in the case of metal, truncation, and limited angle artifacts. The authors propose a generalized correction method for different kinds of artifacts resulting from missing or corrupt data by making use of available prior knowledge to perform data completion.

METHODS

The proposed prior-based artifact correction (PBAC) method requires prior knowledge in form of a planning CT of the same patient or in form of a CT scan of a different patient showing the same body region. In both cases, the prior image is registered to the patient image using a deformable transformation. The registered prior is forward projected and data completion of the patient projections is performed using smooth sinogram inpainting. The obtained projection data are used to reconstruct the corrected image.

RESULTS

The authors investigate metal and truncation artifacts in patient data sets acquired with a clinical CT and limited angle artifacts in an anthropomorphic head phantom data set acquired with a gantry-based flat detector CT device. In all cases, the corrected images obtained by PBAC are nearly artifact-free. Compared to conventional correction methods, PBAC achieves better artifact suppression while preserving the patient-specific anatomy at the same time. Further, the authors show that prominent anatomical details in the prior image seem to have only minor impact on the correction result.

CONCLUSIONS

The results show that PBAC has the potential to effectively correct for metal, truncation, and limited angle artifacts if adequate prior data are available. Since the proposed method makes use of a generalized algorithm, PBAC may also be applicable to other artifacts resulting from missing or corrupt data.

Post-processing sets of tilted CT volumes as a method for metal artifact reduction

Background

Metal implants, surgical clips and other foreign bodies may cause ‘streaking’ or ‘star’ artifacts in computed tomography (CT) reconstructions, for example in the vicinity of dental restorations or hip implants. The deteriorated image quality complicates contouring and has an adverse effect on quantitative planning in external beam therapy.

Methods

The potential to reduce artifacts by acquisition of tilted CT reconstructions from different angles of the same object was investigated. While each of those reconstructions still contained artifacts, they were not necessarily in the same place in each CT. By combining such CTs with complementary information, a reconstructed volume with less or even without artifacts was obtained. The most straightforward way to combine the co-registered volumes was to calculate the mean or median per voxel. The method was tested with a calibration phantom featuring a titanium insert, and with a human skull featuring multiple dental restorations made from gold and steel. The performance of the method was compared to established metal artifact reduction (MAR) algorithms. Dose reduction was tested.

Results

In a visual comparison, streaking artifacts were strongly reduced and details in the vicinity of metal foreign bodies became much more visible. In case of the calibration phantom, average bias in Hounsfield units was reduced by 94% and per-voxel-errors and noise were reduced by 83%. In case of the human skull, bias was reduced by 95% and noise was reduced by 94%. The performance of the method was visually superior and quantitatively compareable to established MAR algorithms. Dose reduction was viable.

Conclusions

A simple post-processing method for MAR was described which required one or more complementary scans but did not rely on any a priori information. The method was computationally inexpensive. Performance of the method was quantitatively comparable to established algorithms and visually superior in a direct comparison. Dose reduction was demonstrated, artifacts could be reduced without compromising total dose to the patient.

Peering through the glare: using dual-energy CT to overcome the problem of metal artefacts in bone radiology

OBJECTIVE

Imaging of patients with large metal implants remains one of the most difficult endeavours for radiologists. This article reviews the theory of dual-energy CT (DECT) and its ability to reduce metal artefact, thus enhancing the diagnostic value of musculoskeletal imaging. The strengths, weaknesses, and alternative applications of DECT, as well as areas requiring further research, will also be reviewed.

CONCLUSION

Currently, DECT stands as the frontier for metal artefact reduction in musculoskeletal imaging. DECT requires no additional radiation and provides significantly enhanced image acquisition. When considered along with its other capabilities, DECT is a promising new tool for musculoskeletal and trauma radiologists.

Metal artifact reduction in CT using fusion based prior image

PURPOSE

In computed tomography, metallic objects in the scanning field create the so-called metal artifacts in the reconstructed images. Interpolation-based methods for metal artifact reduction (MAR) replace the metal-corrupted projection data with surrogate data obtained from interpolation using the surrounding uncorrupted sinogram information. Prior-based MAR methods further improve interpolation-based methods by better estimating the surrogate data using forward projections from a prior image. However, the prior images in most existing prior-based methods are obtained from segmented images and misclassification in segmentation often leads to residual artifacts and tissue structure loss in the final corrected images. To overcome these drawbacks, the authors propose a fusion scheme, named fusion prior-based MAR (FP-MAR).

METHODS

The FP-MAR method consists of (i) precorrect the image by means of an interpolation-based MAR method and an edge-preserving blur filter; (ii) generate a prior image from the fusion of this precorrected image and the originally reconstructed image with metal parts removed; (iii) forward project this prior image to guide the estimation of the surrogate data using well-developed replacement techniques.

RESULTS

Both simulations and clinical image tests are carried out to show that the proposed FP-MAR method can effectively reduce metal artifacts. A comparison with other MAR methods demonstrates that the FP-MAR method performs better in artifact suppression and tissue feature preservation.

CONCLUSIONS

From a wide range of clinical cases to which FP-MAR has been tested (single or multiple pieces of metal, various shapes, and sizes), it can be concluded that the proposed fusion based prior image preserves more tissue information than other segmentation-based prior approaches and can provide better estimates of the surrogate data in prior-based MAR methods.

Sequentially reweighted TV minimization for CT metal artifact reduction

PURPOSE

Metal artifact reduction has long been an important topic in x-ray CT image reconstruction. In this work, the authors propose an iterative method that sequentially minimizes a reweighted total variation (TV) of the image and produces substantially artifact-reduced reconstructions.

METHODS

A sequentially reweighted TV minimization algorithm is proposed to fully exploit the sparseness of image gradients (IG). The authors first formulate a constrained optimization model that minimizes a weighted TV of the image, subject to the constraint that the estimated projection data are within a specified tolerance of the available projection measurements, with image non-negativity enforced. The authors then solve a sequence of weighted TV minimization problems where weights used for the next iteration are computed from the current solution. Using the complete projection data, the algorithm first reconstructs an image from which a binary metal image can be extracted. Forward projection of the binary image identifies metal traces in the projection space. The metal-free background image is then reconstructed from the metal-trace-excluded projection data by employing a different set of weights. Each minimization problem is solved using a gradient method that alternates projection-onto-convex-sets and steepest descent. A series of simulation and experimental studies are performed to evaluate the proposed approach.

RESULTS

Our study shows that the sequentially reweighted scheme, by altering a single parameter in the weighting function, flexibly controls the sparsity of the IG and reconstructs artifacts-free images in a two-stage process. It successfully produces images with significantly reduced streak artifacts, suppressed noise and well-preserved contrast and edge properties.

CONCLUSIONS

The sequentially reweighed TV minimization provides a systematic approach for suppressing CT metal artifacts. The technique can also be generalized to other "missing data" problems in CT image reconstruction.

A hybrid metal artifact reduction algorithm for x-ray CT

PURPOSE

Presence of metal artifacts is a major reason of degradation of computed tomography image quality and there is still no standard solution to this issue. A class of recently investigated metal artifact reduction (MAR) methods based on forward projection of a prior image that is artifact-free to replace the metal affected projection data have shown promising results. However, usually it is hard to get a good prior image which is close to the true image without artifacts. This work aims at creating a good prior image so that the forward projection can replace the metal affected projection data well.

METHODS

The proposed method consists of four steps based on the forward projection MAR framework. First, metal implants in the reconstructed image are segmented and the corresponding metal traces in the projection domain are identified. Then the prior image is obtained by two steps. A processed precorrected image is generated as an initial prior image first and then in the next step it is used as the initial image of the iterative reconstruction from the unaffected projection data to generate a better prior image. In order to deal with severe artifacts, the iteration incorporates the total variation minimization constraint as well as a novel constraint which forces the soft tissue region near metal to be as flat as possible. Finally, the projection is completed using forward projection of the prior image and the corrected image is reconstructed by FBP. A linear interpolation MAR method and two recently reported forward projection based methods are performed simultaneously for comparison.

RESULTS

The proposed method shows outstanding performance on both phantoms' and patients' datasets. This approach can reduce artifacts dramatically and restore tissue structures near metal to a large extent. Unlike competing MAR methods, it can effectively prevent introduction of new artifacts and false structures. Moreover, the proposed method has the lowest RMSE in regions of both soft tissue and bone tissue among the corrected images and is ranked as the best method for evaluation, by radiologists.

CONCLUSIONS

Both subjective and quantitative evaluations of the results demonstrate the superior performance of the proposed algorithm, compared to that of the competing methods. This method offers a remarkable improvement of the image quality.

X-ray CT metal artifact reduction using wavelet domain L0 sparse regularization

X-ray computed tomography (CT) imaging of patients with metallic implants usually suffers from streaking metal artifacts. In this paper, we propose a new projection completion metal artifact reduction (MAR) algorithm by formulating the completion of missing projections as a regularized inverse problem in the wavelet domain. The Douglas-Rachford splitting (DRS) algorithm was used to iteratively solve the problem. Two types of prior information were exploited in the algorithm: 1) the sparsity of the wavelet coefficients of CT sinograms in a dictionary of translation-invariant wavelets and 2) the detail wavelet coefficients of a prior sinogram obtained from the forward projection of a segmented CT image. A pseudo- L0 synthesis prior was utilized to exploit and promote the sparsity of wavelet coefficients. The proposed L0-DRS MAR algorithm was compared with standard linear interpolation and the normalized metal artifact reduction (NMAR) approach proposed by Meyer using both simulated and clinical studies including hip prostheses, dental fillings, spine fixation and electroencephalogram electrodes in brain imaging. The qualitative and quantitative evaluations showed that our algorithm substantially suppresses streaking artifacts and can outperform both linear interpolation and NMAR algorithms.

A novel scheme to design the filter for CT reconstruction using FBP algorithm

Background

The Filtered Back-Projection (FBP) algorithm is the most important technique for computerized tomographic (CT) imaging, in which the ramp filter plays a key role. FBP algorithm had been derived using the continuous system model. However, it has to be discretized in practical applications, which necessarily produces distortion in the reconstructed images.

Methods

A novel scheme is proposed to design the filters to substitute the standard ramp filter to improve the reconstruction performance for parallel beam tomography. The design scheme is presented under the discrete image model and discrete projection environment. The designs are achieved by constrained optimization procedures. The designed filter can be regarded as the optimal filter for the corresponding parameters in some ways.

Results

Some filters under given parameters (such as image size and scanning angles) have been designed. The performance evaluation of CT reconstruction shows that the designed filters are better than the ramp filter in term of some general criteria.

Conclusions

The 2-D or 3-D FBP algorithms for fan beam tomography used in most CT systems, are obtained by modifying the FBP algorithm for parallel beam tomography. Therefore, the designed filters can be used for fan beam tomography and have potential applications in practical CT systems.

Reduction of coil mass artifacts in high-resolution flat detector conebeam CT of cerebral stent-assisted coiling

BACKGROUND AND PURPOSE

Developments in flat panel angiographic C-arm systems have enabled visualization of both the neurovascular stents and host arteries in great detail, providing complementary spatial information in addition to conventional DSA. However, the visibility of these structures may be impeded by artifacts generated by adjacent radio-attenuating objects. We report on the use of a metal artifact reduction algorithm for high-resolution contrast-enhanced conebeam CT for follow-up imaging of stent-assisted coil embolization.

MATERIALS AND METHODS

Contrast-enhanced conebeam CT data were acquired in 25 patients who underwent stent-assisted coiling. Reconstructions were generated with and without metal artifact reduction and were reviewed by 3 experienced neuroradiologists by use of a 3-point scale.

RESULTS

With metal artifact reduction, the observers agreed that the visibility had improved by at least 1 point on the scoring scale in >40% of the cases (κ = 0.6) and that the streak artifact was not obscuring surrounding structures in 64% of all cases (κ = 0.6). Metal artifact reduction improved the image quality, which allowed for visibility sufficient for evaluation in 65% of the cases, and was preferred over no metal artifact reduction in 92% (κ = 0.9). Significantly higher scores were given with metal artifact reduction (P < .0001).

CONCLUSIONS

Although metal artifact reduction is not capable of fully removing artifacts caused by implants with high x-ray absorption, we have shown that the image quality of contrast-enhanced conebeam CT data are improved drastically. The impact of the artifacts on the visibility varied between cases, and yet the overall visibility of the contrast-enhanced conebeam CT with metal artifact reduction improved in most the cases.

Metal artifacts reduction using monochromatic images from spectral CT: evaluation of pedicle screws in patients with scoliosis

PURPOSE

To evaluate the effectiveness of spectral CT in reducing metal artifacts caused by pedicle screws in patients with scoliosis.

MATERIALS AND METHODS

Institutional review committee approval and written informed consents from patients were obtained. 18 scoliotic patients with a total of 228 pedicle screws who underwent spectral CT imaging were included in this study. Monochromatic image sets with and without the additional metal artifacts reduction software (MARS) correction were generated with photon energy at 65keV and from 70 to 140keV with 10keV interval using the 80kVp and 140kVp projection sets. Polychromatic images corresponded to the conventional 140kVp imaging were also generated from the same scan data as a control group. Both objective evaluation (screw width and quantitative artifacts index measurements) and subjective evaluation (depiction of pedicle screws, surrounding structures and their relationship) were performed.

RESULTS

Image quality of monochromatic images in the range from 110 to 140keV (0.97±0.28) was rated superior to the conventional polychromatic images (2.53±0.54) and also better than monochromatic images with lower energy. Images of energy above 100keV also give accurate measurement of the width of screws and relatively low artifacts index. The form of screws was slightly distorted in MARS reconstruction.

CONCLUSIONS

Compared to conventional polychromatic images, monochromatic images acquired from dual-energy CT provided superior image quality with much reduced metal artifacts of pedicle screws in patients with scoliosis. Optimal energy range was found between 110 and 140keV.

MR-driven metal artifact reduction in PET/CT

Among the proposed system architectures capable of delivering positron emission tomography/magnetic resonance (PET/MR) datasets, tri-modality systems open an interesting field in which the synergies between these modalities can be exploited to address some of the problems encountered in standalone systems. In this paper we present a feasibility study of the correction of dental streak artifacts in computed tomography (CT)-based attenuation correction images using complementary MR data. The frequency and severity of metal artifacts in oncology patients was studied by inspecting the CT scans of 152 patients examined at our hospital. A prospective correction algorithm using CT and MR information to automatically locate and edit the region affected by metal artifacts was developed and tested retrospectively on data from 15 oncology patients referred for a PET/CT scan. In datasets without malignancies, the activity in Waldeyer's ring was used to measure the maximum uptake variation when the proposed correction was applied. The measured bias ranged from 10% to 30%. In datasets with malignancies on the slices affected by artifacts, the correction led to lesion uptake variations of 6.1% for a lesion 3 cm away from the implant, 1.5% for a lesion 7 cm away and <1% for a lesion 8 cm away.

Clinical evaluation of a commercial orthopedic metal artifact reduction tool for CT simulations in radiation therapy

PURPOSE

Severe artifacts in kilovoltage-CT simulation images caused by large metallic implants can significantly degrade the conspicuity and apparent CT Hounsfield number of targets and anatomic structures, jeopardize the confidence of anatomical segmentation, and introduce inaccuracies into the radiation therapy treatment planning process. This study evaluated the performance of the first commercial orthopedic metal artifact reduction function (O-MAR) for radiation therapy, and investigated its clinical applications in treatment planning.

METHODS

Both phantom and clinical data were used for the evaluation. The CIRS electron density phantom with known physical (and electron) density plugs and removable titanium implants was scanned on a Philips Brilliance Big Bore 16-slice CT simulator. The CT Hounsfield numbers of density plugs on both uncorrected and O-MAR corrected images were compared. Treatment planning accuracy was evaluated by comparing simulated dose distributions computed using the true density images, uncorrected images, and O-MAR corrected images. Ten CT image sets of patients with large hip implants were processed with the O-MAR function and evaluated by two radiation oncologists using a five-point score for overall image quality, anatomical conspicuity, and CT Hounsfield number accuracy. By utilizing the same structure contours delineated from the O-MAR corrected images, clinical IMRT treatment plans for five patients were computed on the uncorrected and O-MAR corrected images, respectively, and compared.

RESULTS

Results of the phantom study indicated that CT Hounsfield number accuracy and noise were improved on the O-MAR corrected images, especially for images with bilateral metal implants. The γ pass rates of the simulated dose distributions computed on the uncorrected and O-MAR corrected images referenced to those of the true densities were higher than 99.9% (even when using 1% and 3 mm distance-to-agreement criterion), suggesting that dose distributions were clinically identical. In all patient cases, radiation oncologists rated O-MAR corrected images as higher quality. Formerly obscured critical structures were able to be visualized. The overall image quality and the conspicuity in critical organs were significantly improved compared with the uncorrected images: overall quality score (1.35 vs 3.25, P = 0.0022); bladder (2.15 vs 3.7, P = 0.0023); prostate and seminal vesicles∕vagina (1.3 vs 3.275, P = 0.0020); rectum (2.8 vs 3.9, P = 0.0021). The noise levels of the selected ROIs were reduced from 93.7 to 38.2 HU. On most cases (8∕10), the average CT Hounsfield numbers of the prostate∕vagina on the O-MAR corrected images were closer to the referenced value (41.2 HU, an average measured from patients without metal implants) than those on the uncorrected images. High γ pass rates of the five IMRT dose distribution pairs indicated that the dose distributions were not significantly affected by the CT image improvements.

CONCLUSIONS

Overall, this study indicated that the O-MAR function can remarkably reduce metal artifacts and improve both CT Hounsfield number accuracy and target and critical structure visualization. Although there was no significant impact of the O-MAR algorithm on the calculated dose distributions, we suggest that O-MAR corrected images are more suitable for the entire treatment planning process by offering better anatomical structure visualization, improving radiation oncologists' confidence in target delineation, and by avoiding subjective density overrides of artifact regions on uncorrected images.

A fully 3D approach for metal artifact reduction in computed tomography

PURPOSE

In computed tomography imaging metal objects in the region of interest introduce inconsistencies during data acquisition. Reconstructing these data leads to an image in spatial domain including star-shaped or stripe-like artifacts. In order to enhance the quality of the resulting image the influence of the metal objects can be reduced. Here, a metal artifact reduction (MAR) approach is proposed that is based on a recomputation of the inconsistent projection data using a fully three-dimensional Fourier-based interpolation. The success of the projection space restoration depends sensitively on a sensible continuation of neighboring structures into the recomputed area. Fortunately, structural information of the entire data is inherently included in the Fourier space of the data. This can be used for a reasonable recomputation of the inconsistent projection data.

METHODS

The key step of the proposed MAR strategy is the recomputation of the inconsistent projection data based on an interpolation using nonequispaced fast Fourier transforms (NFFT). The NFFT interpolation can be applied in arbitrary dimension. The approach overcomes the problem of adequate neighborhood definitions on irregular grids, since this is inherently given through the usage of higher dimensional Fourier transforms. Here, applications up to the third interpolation dimension are presented and validated. Furthermore, prior knowledge may be included by an appropriate damping of the transform during the interpolation step. This MAR method is applicable on each angular view of a detector row, on two-dimensional projection data as well as on three-dimensional projection data, e.g., a set of sequential acquisitions at different spatial positions, projection data of a spiral acquisition, or cone-beam projection data.

RESULTS

Results of the novel MAR scheme based on one-, two-, and three-dimensional NFFT interpolations are presented. All results are compared in projection data space and spatial domain with the well-known one-dimensional linear interpolation strategy.

CONCLUSIONS

In conclusion, it is recommended to include as much spatial information into the recomputation step as possible. This is realized by increasing the dimension of the NFFT. The resulting image quality can be enhanced considerably.

Metal artifact reduction by dual-energy computed tomography using energetic extrapolation: a systematically optimized protocol

OBJECTIVES

Energetic extrapolation is a promising strategy to reduce metal artifacts in dual-source computed tomography (DSCT). We performed this study to systematically optimize image acquisition parameters for this approach in a hip phantom and assess its value in a clinical study.

MATERIALS AND METHODS

Titanium and steel hip prostheses were placed in a standard hip phantom and a water tank and scanned on a DSCT scanner. Tube spectra, tube current ratio, collimation, pitch, and rotation time were optimized in a stepwise process. Artifacts were quantified by measuring the standard deviation of the computed tomography density in a doughnut-shaped region of interest placed around the prosthesis. A total of 22 adult individuals with metallic implants referred for computed tomography for a musculoskeletal indication were scanned using the optimized protocol. Degree of artifacts and diagnostic image quality were rated visually (0-10) and maximum streak intensity was measured.

RESULTS

Sn140/100 kVp proved superior to Sn140/80 kVp. There was a benefit for increasing tube current ratio from 1:1 to 3:1, but not beyond, in favor of the Sn140 kVp spectrum. Artifacts were less severe for a collimation of 32 × 0.6 mm as compared with 40 × 0.6 mm. A pitch of 0.5 at a rotation time of 0.5 seconds per rotation was preferable to other combinations with comparable scanning times. In the clinical study, increasing the extrapolated photon energy from 64 to 120 keV decreased the severity of artifacts from 8.0 to 2.0 (P < 0.001) and decreased streak intensity from 871 to 153 HU (P < 0.001). The median diagnostic image quality rating improved from 2.5 to 8.0 (P < 0.001). The median energy level visually perceived as optimal for diagnostic evaluation was 113 keV (range, 100-130 keV).

CONCLUSIONS

Sn140/100 kVp with a tube current ratio of 3:1, a collimation of 32 × 0.6 mm, and extrapolated energies of 105 to 120 keV are optimal parameters for a dedicated DSCT protocol that effectively reduces metal artifacts by energetic extrapolation. The protocol effectively reduces metal artifacts in all types of metal implants. The optimized reconstructions yielded relevant additional findings.

Cone beam computed tomographic imaging: perspective, challenges, and the impact of near-trend future applications

Cone beam computed tomography (CBCT) can be considered as a valuable imaging modality for improving diagnosis and treatment planning to achieve true guidance for several craniofacial surgical interventions. A new concept and perspective in medical informatics is the highlight discussion about the new imaging interactive workflow. The aim of this article was to present, in a short literature review, the usefulness of CBCT technology as an important alternative imaging modality, highlighting current practices and near-term future applications in cutting-edge thought-provoking perspectives for craniofacial surgical assessment. This article explains the state of the art of CBCT improvements, medical workstation, and perspectives of the dedicated unique hardware and software, which can be used from the CBCT source. In conclusion, CBCT technology is developing rapidly, and many advances are on the horizon. Further progress in medical workstations, engineering capabilities, and improvement in independent software-some open source-should be attempted with this new imaging method. The perspectives, challenges, and pitfalls in CBCT will be delineated and evaluated along with the technological developments.

Frequency split metal artifact reduction (FSMAR) in computed tomography

PURPOSE

The problem of metal artifact reduction (MAR) is almost as old as the clinical use of computed tomography itself. When metal implants are present in the field of measurement, severe artifacts degrade the image quality and the diagnostic value of CT images. Up to now, no generally accepted solution to this issue has been found. In this work, a method based on a new MAR concept is presented: frequency split metal artifact reduction (FSMAR). It ensures efficient reduction of metal artifacts at high image quality with enhanced preservation of details close to metal implants.

METHODS

FSMAR combines a raw data inpainting-based MAR method with an image-based frequency split approach. Many typical methods for metal artifact reduction are inpainting-based MAR methods and simply replace unreliable parts of the projection data, for example, by linear interpolation. Frequency split approaches were used in CT, for example, by combining two reconstruction methods in order to reduce cone-beam artifacts. FSMAR combines the high frequencies of an uncorrected image, where all available data were used for the reconstruction with the more reliable low frequencies of an image which was corrected with an inpainting-based MAR method. The algorithm is tested in combination with normalized metal artifact reduction (NMAR) and with a standard inpainting-based MAR approach. NMAR is a more sophisticated inpainting-based MAR method, which introduces less new artifacts which may result from interpolation errors. A quantitative evaluation was performed using the examples of a simulation of the XCAT phantom and a scan of a spine phantom. Further evaluation includes patients with different types of metal implants: hip prostheses, dental fillings, neurocoil, and spine fixation, which were scanned with a modern clinical dual source CT scanner.

RESULTS

FSMAR ensures sharp edges and a preservation of anatomical details which is in many cases better than after applying an inpainting-based MAR method only. In contrast to other MAR methods, FSMAR yields images without the usual blurring close to implants.

CONCLUSIONS

FSMAR should be used together with NMAR, a combination which ensures an accurate correction of both high and low frequencies. The algorithm is computationally inexpensive compared to iterative methods and methods with complex inpainting schemes. No parameters were chosen manually; it is ready for an application in clinical routine.

CT metal artifact reduction method correcting for beam hardening and missing projections

We present and validate a computed tomography (CT) metal artifact reduction method that is effective for a wide spectrum of clinical implant materials. Projections through low-Z implants such as titanium were corrected using a novel physics correction algorithm that reduces beam hardening errors. In the case of high-Z implants (dental fillings, gold, platinum), projections through the implant were considered missing and regularized iterative reconstruction was performed. Both algorithms were combined if multiple implant materials were present. For comparison, a conventional projection interpolation method was implemented. In a blinded and randomized evaluation, ten radiation oncologists ranked the quality of patient scans on which the different methods were applied. For scans that included low-Z implants, the proposed method was ranked as the best method in 90% of the reviews. It was ranked superior to the original reconstruction (p = 0.0008), conventional projection interpolation (p < 0.0001) and regularized limited data reconstruction (p = 0.0002). All reviewers ranked the method first for scans with high-Z implants, and better as compared to the original reconstruction (p < 0.0001) and projection interpolation (p = 0.004). We conclude that effective reduction of CT metal artifacts can be achieved by combining algorithms tailored to specific types of implant materials.

Qualitative and quantitative assessment of metal artifacts arising from implantable cardiac pacing devices in oncological PET/CT studies: a phantom study

PURPOSE

We evaluate the magnitude of metallic artifacts caused by various implantable cardiac pacing devices (without leads) on both attenuation maps (μ-maps) and positron emission tomography (PET) images using experimental phantom studies. We also assess the efficacy of a metal artifact reduction (MAR) algorithm along with the severity of artifacts in the presence of misalignment between μ-maps and PET images.

METHODS

Four pacing devices including two pacemakers (pacemakers 1 and 2) and two cardiac resynchronization therapy (CRT) devices of pacemaker (CRT-P) and defibrillator (CRT-D) type were placed in three phantoms including a cylindrical Ge-68 phantom, a water-bath phantom and an anthropomorphic heart/thorax phantom. The μ-maps were derived from computed tomography (CT) images reconstructed using the standard method supplied by the manufacturer and those reconstructed using the MAR algorithm. In addition, the standard reconstructed CT images of the last two phantoms were manually misaligned by 10 mm along the patient's axis to simulate misalignment between CT and PET images.

RESULTS

The least and severest artifacts produced on both μ-maps and PET images of the Ge-68 phantom were induced by CRT-P and pacemaker 1 devices, respectively. In the water-bath phantom, CRT-P induced 17.5% over- and 9.2% underestimation of tracer uptake whereas pacemaker 1 induced 69.6% over- and 65.7% underestimation. In the heart/thorax phantom representing a pacemaker-bearing patient, pacemaker 1 induced 41.8% increase and 36.6% decrease in tracer uptake and attenuation coefficients on average in regions corresponding to bright and dark streak artifacts, respectively. Statistical analysis revealed that the MAR algorithm was successful in reducing bright streak artifacts, yet unsuccessful for dark ones. In the heart/thorax phantom, the MAR algorithm reduced the overestimations to 4.4% and the underestimations to 35.5% on average. Misalignment between μ-maps and PET images increased the peak of pseudo-uptake by approximately 20%.

CONCLUSIONS

This study demonstrated that, depending on their elemental composition, different implantable cardiac pacing devices result in varying magnitudes of metal artifacts and thus pseudo-uptake on PET images. The MAR algorithm was not successful in compensating for underestimations which calls for a more efficient algorithm. The results showed that misalignments between PET and CT images render metal-related pseudo-uptake more severe.

Spectral CT with metal artifacts reduction software for improvement of tumor visibility in the vicinity of gold fiducial markers

PURPOSE

To evaluate spectral computed tomography (CT) with metal artifacts reduction software (MARS) for reduction of metal artifacts associated with gold fiducial seeds.

MATERIALS AND METHODS

Thirteen consecutive patients with 37 fiducial seeds implanted for radiation therapy of abdominal lesions were included in this HIPAA-compliant, institutional review board-approved prospective study. Six patients were women (46%) and seven were men (54%). The mean age was 61.1 years (median, 58 years; range, 29-78 years). Spectral imaging was used for arterial phase CT. Images were reconstructed with and without MARS in axial, coronal, and sagittal planes. Two radiologists independently reviewed reconstructions and selected the best image, graded the visibility of the tumor, and assessed the amount of artifacts in all planes. A linear-weighted κ statistic and Wilcoxon signed-rank test were used to assess interobserver variability. Histogram analysis with the Kolmogorov-Smirnov test was used for objective evaluation of artifacts reduction.

RESULTS

Fiducial seeds were placed in pancreas (n = 5), liver (n = 7), periportal lymph nodes (n = 1), and gallbladder bed (n = 1). MARS-reconstructed images received a better grade than those with standard reconstruction in 60% and 65% of patients by the first and second radiologist, respectively. Tumor visibility was graded higher with standard versus MARS reconstruction (grade, 3.7 ± 1.0 vs 2.8 ± 1.1; P = .001). Reduction of blooming was noted on MARS-reconstructed images (P = .01). Amount of artifacts, for both any and near field, was significantly smaller on sagittal and coronal MARS-reconstructed images than on standard reconstructions (P < .001 for all comparisons). Far-field artifacts were more prominent on axial MARS-reconstructed images than on standard reconstructions (P < .01). Linear-weighted κ statistic showed moderate to perfect agreement between radiologists. CT number distribution was narrower with MARS than with standard reconstruction in 35 of 37 patients (P < .001).

CONCLUSION

Spectral CT with use of MARS improved tumor visibility in the vicinity of gold fiducial seeds.

Strategy of computed tomography sinogram inpainting based on sinusoid-like curve decomposition and eigenvector-guided interpolation

Projection incompleteness in x-ray computed tomography (CT) often relates to sparse sampling or detector gaps and leads to degraded reconstructions with severe streak and ring artifacts. To suppress these artifacts, this study develops a new sinogram inpainting strategy based on sinusoid-like curve decomposition and eigenvector-guided interpolation, where each missing sinogram point is considered located within a group of sinusoid-like curves and estimated from eigenvector-guided interpolation to preserve the sinogram texture continuity. The proposed approach is evaluated on real two-dimensional fan-beam CT data, for which the projection incompleteness, due to sparse sampling and symmetric detector gaps, is simulated. A Compute Unified Device Architecture (CUDA)-based parallelization is applied on the operations of sinusoid fittings and interpolations to accelerate the algorithm. A comparative study is then conducted to evaluate the proposed approach with two other inpainting methods and with a compressed sensing iterative reconstruction. Qualitative and quantitative performances demonstrate that the proposed approach can lead to efficient artifact suppression and less structure blurring.

Measuring femoral lesions despite CT metal artefacts: a cadaveric study

OBJECTIVE

Computed tomography is the modality of choice for measuring osteolysis but suffers from metal-induced artefacts obscuring periprosthetic tissues. Previous papers on metal artefact reduction (MAR) show qualitative improvements, but their algorithms have not found acceptance for clinical applications. We investigated to what extent metal artefacts interfere with the segmentation of lesions adjacent to a metal femoral implant and whether metal artefact reduction improves the manual segmentation of such lesions.

MATERIALS AND METHODS

We manually created 27 periprosthetic lesions in 10 human cadaver femora. We filled the lesions with a fibrotic interface tissue substitute. Each femur was fitted with a polished tapered cobalt-chrome prosthesis and imaged twice--once with the metal, and once with a substitute resin prosthesis inserted. Metal-affected CTs were processed using standard back-projection as well as projection interpolation (PI) MAR. Two experienced users segmented all lesions and compared segmentation accuracy.

RESULTS

We achieved accurate delineation of periprosthetic lesions in the metal-free images. The presence of a metal implant led us to underestimate lesion volume and introduced geometrical errors in segmentation boundaries. Although PI MAR reduced streak artefacts, it led to greater underestimation of lesion volume and greater geometrical errors than without its application.

CONCLUSION

CT metal artefacts impair image segmentation. PI MAR can improve subjective image appearance but causes loss of detail and lower image contrast adjacent to prostheses. Our experiments showed that PI MAR is counterproductive for manual segmentation of periprosthetic lesions and should be used with care.

Reference-free ground truth metric for metal artifact evaluation in CT images

PURPOSE

In computed tomography (CT), metal objects in the region of interest introduce data inconsistencies during acquisition. Reconstructing these data results in an image with star shaped artifacts induced by the metal inconsistencies. To enhance image quality, the influence of the metal objects can be reduced by different metal artifact reduction (MAR) strategies. For an adequate evaluation of new MAR approaches a ground truth reference data set is needed. In technical evaluations, where phantoms can be measured with and without metal inserts, ground truth data can easily be obtained by a second reference data acquisition. Obviously, this is not possible for clinical data. Here, an alternative evaluation method is presented without the need of an additionally acquired reference data set.

METHODS

The proposed metric is based on an inherent ground truth for metal artifacts as well as MAR methods comparison, where no reference information in terms of a second acquisition is needed. The method is based on the forward projection of a reconstructed image, which is compared to the actually measured projection data.

RESULTS

The new evaluation technique is performed on phantom and on clinical CT data with and without MAR. The metric results are then compared with methods using a reference data set as well as an expert-based classification. It is shown that the new approach is an adequate quantification technique for artifact strength in reconstructed metal or MAR CT images.

CONCLUSIONS

The presented method works solely on the original projection data itself, which yields some advantages compared to distance measures in image domain using two data sets. Beside this, no parameters have to be manually chosen. The new metric is a useful evaluation alternative when no reference data are available.

Reduction of artefacts caused by hip implants in CT-based attenuation-corrected PET images using 2-D interpolation of a virtual sinogram on an irregular grid

Purpose

Metallic prosthetic replacements, such as hip or knee implants, are known to cause strong streaking artefacts in CT images. These artefacts likely induce over- or underestimation of the activity concentration near the metallic implants when applying CT-based attenuation correction of positron emission tomography (PET) images. Since this degrades the diagnostic quality of the images, metal artefact reduction (MAR) prior to attenuation correction is required.

Methods

The proposed MAR method, referred to as virtual sinogram-based technique, replaces the projection bins of the sinogram that are influenced by metallic implants by a 2-D Clough-Tocher cubic interpolation scheme performed in an irregular grid, called Delaunay triangulated grid. To assess the performance of the proposed method, a physical phantom and 30 clinical PET/CT studies including hip prostheses were used. The results were compared to the method implemented on the Siemens Biograph mCT PET/CT scanner.

Results

Both phantom and clinical studies revealed that the proposed method performs equally well as the Siemens MAR method in the regions corresponding to bright streaking artefacts and the artefact-free regions. However, in regions corresponding to dark streaking artefacts, the Siemens method does not seem to appropriately correct the tracer uptake while the proposed method consistently increased the uptake in the underestimated regions, thus bringing it to the expected level. This observation is corroborated by the experimental phantom study which demonstrates that the proposed method approaches the true activity concentration more closely.

Conclusion

The proposed MAR method allows more accurate CT-based attenuation correction of PET images and prevents misinterpretation of tracer uptake, which might be biased owing to the propagation of bright and dark streaking artefacts from CT images to the PET data following the attenuation correction procedure.

Efficient CT metal artifact reduction based on fractional-order curvature diffusion

We propose a novel metal artifact reduction method based on a fractional-order curvature driven diffusion model for X-ray computed tomography. Our method treats projection data with metal regions as a damaged image and uses the fractional-order curvature-driven diffusion model to recover the lost information caused by the metal region. The numerical scheme for our method is also analyzed. We use the peak signal-to-noise ratio as a reference measure. The simulation results demonstrate that our method achieves better performance than existing projection interpolation methods, including linear interpolation and total variation.

An opposite view data replacement approach for reducing artifacts due to metallic dental objects

PURPOSE

To present a conceptually new method for metal artifact reduction (MAR) that can be used on patients with multiple objects within the scan plane that are also of small sized along the longitudinal (scanning) direction, such as dental fillings.

METHODS

The proposed algorithm, named opposite view replacement, achieves MAR by first detecting the projection data affected by metal objects and then replacing the affected projections by the corresponding opposite view projections, which are not affected by metal objects. The authors also applied a fading process to avoid producing any discontinuities in the boundary of the affected projection areas in the sinogram. A skull phantom with and without a variety of dental metal inserts was made to extract the performance metric of the algorithm. A head and neck case, typical of IMRT planning, was also tested.

RESULTS

The reconstructed CT images based on this new replacement scheme show a significant improvement in image quality for patients with metallic dental objects compared to the MAR algorithms based on the interpolation scheme. For the phantom, the authors showed that the artifact reduction algorithm can efficiently recover the CT numbers in the area next to the metallic objects.

CONCLUSIONS

The authors presented a new and efficient method for artifact reduction due to multiple small metallic objects. The obtained results from phantoms and clinical cases fully validate the proposed approach.

Metal artifact reduction in cone beam computed tomography using forward projected reconstruction information

In this work we present a new method to reduce artifacts, produced by high-density objects, especially metal implants, in X-ray cone beam computed tomography (CBCT). These artifacts influence clinical diagnostics and treatments using CT data, if metal objects are located in the field of view (FOV). Our novel method reduces metal artifacts by virtually replacing the metal objects with tissue objects of the same shape. First, the considered objects must be segmented in the original 2D projection data as well as in a reconstructed 3D volume. The attenuation coefficients of the segmented voxels are replaced with adequate attenuation coefficients of tissue (or water), then the required parts of the volume are projected onto the segmented 2D pixels, to replace the original information. This corrected 2D data can then be reconstructed with reduced artifacts, i. e. all metal objects virtually vanished. After the reconstruction, the segmented 3D metal objects were re-inserted into the corrected 3D volume. Our method was developed for mobile C-arm CBCTs; as it is necessary that they are of low weight, the C-arm results in unpredictable distortion. This misalignment between the original 2D data and the forward projection of the reconstructed 3D volume must be adjusted before the correction of the segmented 2D pixels. We applied this technique to clinical data and will now present the results.

An algorithm for efficient metal artifact reductions in permanent seed

PURPOSE

In permanent seed implants, 60 to more than 100 small metal capsules are inserted in the prostate, creating artifacts in x-ray computed tomography (CT) imaging. The goal of this work is to develop an automatic method for metal artifact reduction (MAR) from small objects such as brachytherapy seeds for clinical applications.

METHODS

The approach for MAR is based on the interpolation of missing projections by directly using raw helical CT data (sinogram). First, an initial image is reconstructed from the raw CT data. Then, the metal objects segmented from the reconstructed image are reprojected back into the sinogram space to produce a metal-only sinogram. The Steger method is used to determine precisely the position and edges of the seed traces in the raw CT data. By combining the use of Steger detection and reprojections, the missing projections are detected and replaced by interpolation of non-missing neighboring projections.

RESULTS

In both phantom experiments and patient studies, the missing projections have been detected successfully and the artifacts caused by metallic objects have been substantially reduced. The performance of the algorithm has been quantified by comparing the uniformity between the uncorrected and the corrected phantom images. The results of the artifact reduction algorithm are indistinguishable from the true background value.

CONCLUSIONS

An efficient algorithm for MAR in seed brachytherapy was developed. The test results obtained using raw helical CT data for both phantom and clinical cases have demonstrated that the proposed MAR method is capable of accurately detecting and correcting artifacts caused by a large number of very small metal objects (seeds) in sinogram space. This should enable a more accurate use of advanced brachytherapy dose calculations, such as Monte Carlo simulations.

Metal artifact suppression from reformatted projections in multislice helical CT using dual-front active contours

PURPOSE

Large metallic implants, such as hip prosthesis and shoulder implants, can cause severe artifacts in CT exams. As such, there have been significant efforts on the design of various image- or projection-based correction methods or iterative reconstruction methods with the hope to reconstruct artifact-free images. Unfortunately, suppression of metal artifacts remains a very challenging problem, in which metal region segmentation is one of the most important steps in assuring the efficiency of artifact suppression. In this article, the authors propose a novel, semiautomatic metal region segmentation algorithm based on a dual-front active contour model and a boundary mapping strategy to detect multiple large metal implants on reformatted projection data and to effectively suppress or eliminate metal artifacts on reconstructed images.

METHODS

First, the projections created from helical scan data were reformatted by combining data at the same view angle over the full longitudinal scan range. In this way, the shape, location, and number of the metal structures show up clearly on each reformatted projection, changing only slightly between adjacent projections. Second, an initial boundary on one of the reformatted projections is defined, and a boundary mapping strategy was utilized to map the metal boundary on the first reformatted projection to the next adjacent projection. Third, a novel dual-front active contour model was used to evolve the mapped boundary from the prior projection to the actual boundary in the current projection. By iteratively performing the boundary mapping and boundary evolution procedure, the metal structures (one or multiple) on all the projections can be extracted efficiently and accurately. Finally, a Delaunay triangulation was applied to fill the metal shadows and the corrected projection data were reconstructed with a commercially available algorithm.

RESULTS

Experimental studies on clinical hip and shoulder CT exams and a comparison with a gradient-based threshold method were performed. The results demonstrated that the proposed segmentation strategy was able to segment multiple metal implants more accurately than the threshold method. Soft-tissue visibility was improved dramatically.

CONCLUSIONS

In total, the artifacts caused by dense metal implants were suppressed dramatically with the proposed metal artifact suppression technique.