Artifact Reduction Algorithm Research Articles

The value of iterative metal artifact reduction algorithms during antenna positioning for CT-guided microwave ablation

Objectives: To compare image quality between filtered back projection (FBP) and iterative reconstruction algorithm and dedicated metal artifact reduction (iMAR) algorithms during antenna positioning for computed tomography-guided microwave ablation (MWA).Materials and methods: An MWA antenna was positioned in the liver of five pigs under CT guidance. Different exposure settings (120kVp/200mAs-120kVp/50mAs) and image reconstruction techniques (FBP, iterative reconstruction with and without iMAR) were applied. Quantitative image analysis included density measurements in six positions (e.g., liver in extension of the antenna [ANTENNA] and liver >3 cm away from the antenna [LIVER-1]). Qualitative image analysis included assessment of overall quality, image noise, artifacts at the antenna tip, artifacts in liver parenchyma bordering antenna tip and newly generated artifacts. Two independent observers performed the analyses twice and interreader agreement was compared with Bland–Altman analysis.Results: For all exposure and reconstruction settings, density measurements for ANTENNA were significantly higher for the I30-1 iMAR compared with FBP and I30-1 (e.g., 8.3−17.2HU vs. −104.5 to 155.1HU; p ≤ 0.01, respectively). In contrast, for all exposure settings, density measurements for LIVER-1 were comparable between FBP and I30-1 iMAR (e.g., 49.4−50.4HU vs. 50.1−52.5U, respectively). For all exposure and reconstruction settings, subjective image quality for LIVER-1 was better for the I30-1 iMAR algorithm compared with FBP and I30-1. Bland–Altman interobserver agreement was from −0.2 to 0.2 for FBP and iMAR, and Cohen’s kappa was 0.74.Conclusion: Iterative algorithms I30-1 with iMAR algorithm improves image quality during antenna positioning and placement for CT-guided MWA and is applicable over a range of exposure settings.

Effect of applying metal artifact reduction algorithm in cone beam computed tomography in detection of vertical root fractures of teeth with metallic post versus digital intraoral radiography

Background: Conventional radiographs are not an efficient diagnostic imaging modality to detect vertical root fracture. Cone-beam computed tomography (CBCT) is a three-dimensional imaging modality that overcomes the limitations of conventional radiography in the detection of vertical root fractures (VRFS), although metallic structures produce artifacts in the produced images and since most of the teeth with VRF are endodontically treated and have metallic posts in root canal so fracture detection may be difficult. Aim: This study aimed to determine the diagnostic accuracy of CBCT using metal artifact reduction algorithm in detection of VRF of teeth with metallic posts compared to digital intraoral radiography. Materials and Methods: One hundred and twenty single-rooted extracted human teeth were endodontically treated then placed in an acrylic block and metallic posts were inserted. The teeth roots were divided into two groups; one with induced VRF and the other having intact roots. Then, each tooth was coded and imaged three times using CBCT with and without metal artifact reduction algorithm and digital periapical radiography. Data were collected and statistically analyzed. Results: Digital periapical radiography showed statistically significantly lower diagnostic accuracy than CBCT modalities (P ≤ 0.05). The use of metal artifact reduction algorithm improved the diagnostic accuracy from CBCT1 to CBCT2 but with no statistically significant difference (P ≥ 0.05). Conclusion: From the study, we can conclude that in case of presence of metallic posts, CBCT with metal artifact reduction algorithm can improve detection of VRF.

Application of a multi-material artifact reduction algorithm in a wide-detector CT in the evaluation of the portal venous angiography of postoperative TIPS and embolization

Objective: To assess the effect of monochromatic images and metal artifact reduction (MAR) on the image quality of spectral CT portal venous angiography in patients with operation of after the performing transjugular intrahepatic portosystemic stent shunt(TIPS) and embolization. Methods: From December 2017 to April 2018, the examination data of 28 patients with portal hypertension due to cirrhosis who underwent portal vein angiography 1 month after TIPS and embolization were prospectively collected. After spectral CT scanning in revolution CT, the monochromatic energy levels(60 keV, 120 keV), 60 keV + 120 keV, 120kV-like + 120 keV fused images combined with MAR algorithm were reconstructed. Quantitative parameters such as image artifact index (AI) and qualitative visual evaluation scores were recorded and compared. Results: The 120 keV monochromatic images showed the lowest AI value(30.8±8.5, 18.2±4.3) and highest metal artifacts reduction effect. The 60 keV monochromatic images showed the highest AI value (57.3±15.7, 32.1±7.9) and the lowest metal artifacts reduction effect. The AI value of 60 keV + 120 keV fused images was lower than that of 60 keV images(26.2%, 24.7%). The difference of AI value between each group was statistically significant(all P<0.05). The interobserver agreement in the subjective image scores was moderate with kappa value of 0.824. The overall image quality score of 60 keV + 120 keV fused image and the noise score of 120 kV-like+120 keV were higher than the remaining groups. The differences of the subjective scores among each group were statistically significant(all P<0.05). Conclusion: The spectral CT with MAR algorithm can effectively improve the image quality of portal vein angiography after the TIPS and embolization therapy and the 60 keV + 120 keV fused images can eliminate artifacts and ensure a clear display of blood vessels.

Ability to detect endodontic complications using three different cone beam computed tomography units with and without artefact reduction modes: an exvivo study.

To assess observer performance in detectingendodontic complications using three different cone beam computed tomography (CBCT) units with and without the application of artefact reduction modes. The study involved 40 freshly extracted human mandibular teeth (n=10 per group) and divided randomly into four endodontic complication groups. Group 1) Instrument fracture; Group 2) Strip perforation; Group 3) Canal underfilling; and Group 4) Canal overfilling. Images of each tooth were obtained using three different CBCT units offering artefact reduction algorithms: the ProMax 3D Max, the Pax Flex 3D and the Dentri S. Four observers evaluated the images for the presence/absence of the four simulated endodontic complications. Weighted kappa coefficients and intra-class correlation coefficients (ICCs) were calculated to reveal the intra- and inter-observer agreement for each imaging mode, respectively. Receiver operating characteristic (ROC) analysis was used to evaluate the observers' performance. DeLong tests were used to compare the results for each image mode and observer using a significance level of α=0.05. In each of the four simulated endodontic complication groups, no significant differences were observed with and without application of artefact reduction for any of the three CBCT units tested. Only two significant differences were detected, and both were between the ProMax 3D Max at low mode AR and ProMax 3D Max without AR: observer 2 in group 1 (P=0.0001) and observer 4 in group 4 (P=0.0256). For each of the three CBCT units tested, application of artefact reduction for detecting endodontic complications is not recommended as a routine tool.

17 Impact of a CT artifact reduction algorithm in radiotherapy: preliminary qualitative and quantitative aspects

Introduction In radiotherapy, CT images have two main objectives: allow volumes delineation and obtain electron densities for dose calculation. The presence of dense structures such as hip prostheses or dental implants create artifacts that can significantly impair both of these goals. Iterative Metal Artifact Reduction (IMAR) is a metal artifact reduction algorithm developed by Siemens, which greatly facilitates the delimitation of volumes. We studied its impact on the modification of Hounsfield units (HU) as well as the dosimetric consequences for pelvis and head&neck (H&N) regions. Methods All CT acquisitions were made on a Somatom AS 20 Definition (Siemens) at 120 kV, 400 mAs and 2 mm slice thickness. For the pelvic region, we used a phantom composed of a water equivalent material in which we inserted two hip prostheses. For the H&N sphere, we used an anthropomorphic phantom (CIRS Atom 701) with two pieces of lead inserted in the teeth. CT acquisitions were performed with inserts (prostheses or lead), with IMAR reconstruction (imarCT), and without (artefactCT). We used the protocol HIP implants for pelvis and Dental fillings for H&N. A CT acquisitions without insert were also done (baselineCT). Using the Matlab software (V2014), we calculated, in significant regions (between metal inserts), the HU differences between baselineCT and respectively imarCT and artefactCT. In order to estimate the dosimetric impact of these HU variations we performed a treatment planification on both phantoms and on patients with pelvic and dental implants with the treatment planning system V13.6 (Varian). In pelvic we use 4 static fields of 15 MV and in the H&N 2 RapidArc beams of 6 MV. The results are given in terms of mean, standard deviation ( σ ) and most likely value (p). Results For the pelvic area, the HU deviations from the baseline CT are 84 HU (σ = 53 HU, p = 100 HU) and −106 HU (σ = 487 HU, p = 200 HU) respectively for imarCT and artefactCT. For the H&N the HU deviations are 15 HU (σ = 34 HU, p = 0 HU) and 44 HU (σ = 413 HU, p = 200 HU) respectively for imarCT and artefactCT. We note in both cases a spread of HU without IMAR and a slight overestimation of HU with IMAR. The dosimetric impact, based on the comparison between the planification made with imarCT and artefactCT showed for the pelvic area, in the phantom, a dose variation from −11% to 1% with an average of −4.6% (σ = 3%) while in the patient, the variation is between −10.8% and +0.4% with an average of−3.4% (σ = 2.3%). For the H&N area, in the phantom, the difference in dose varies from −10% to 7.4% with an average of −0.6% (σ = 2%), whereas in the patient, the difference in dose varies from −3% to 24% with an average of 0.6% (σ = 2%). Conclusions In addition to being an undeniable aid to delineation, it seems in this preliminary study that IMAR is a significant tool to issue metal artefact problem in calculating dose in patient with metal implants close to treated areas.

Metal Artifact Reduction of Dental Fillings in Head and Neck CT Images

Introduction: The issue of metal artifact and its reduction is as old as the clinical use of computed tomography itself. When metal objects such as dental fillings, hip prostheses or surgical clips are present in the computed tomography (CT) field of view (FOV), make severe artifacts that reduce the image quality and accuracy of CT numbers. They can lead to unreliable clinical results due to inability in true tumor volume delineation and uncertainty in dose calculation of treatment planning software. So far, no generally accepted solution to this problem, especially for small size dental fillings, has been found. Herein, an approach is presented to reduce the dental filling artifacts in CT images of head and neck patients with multiple dental fillings. The proposed approach is compared with the commercial orthopedic metal artifact reduction (O-MAR) algorithm by Philips company. Materials and Methods: Our algorithm consists of six steps: 1) metallic object segmentation by thresholding, 2) obtaining the prior image by multi thresholding of the initial image, 3) normalization of the original image sinogram by prior image, 4) interpolation (replacing the affected projection data by previous slice unaffected projection data, 5) denormalization of the corrected sinogram and 6) application of a two dimensional adaptive filter to the final image. The forth step can be implemented by substitution of affected projections with opposite view projections. Both methods were tested and previous slice substitution was superior. Quantitative evaluation of the commercial and proposed algorithms was done in terms of peak signal-to-noise ratio (PSNR), signal-to- noise ratio (SNR) and structural similarity index (SSIM) on a CT image of a head and neck patient with four dental fillings. The posterior part of the head in original image was considered as the reference image. Also two uniform regions of interest (ROI) were considered in the image. ROI1 was posterior region of the head away from dental fillings, while ROI2 was restricted to the tongue region near to the dental fillings. Results: The PSNR, SNR, SSIM values obtained by the proposed method and O-MAR algorithm were 37.05, 36.13, 22.29, 21.37, 0.93 and 0.84, respectively. Using our approach, the standard deviation of CT numbers in ROI1 was 27 times less than the original image and 7% better than the commercial competitor. However, for ROI2 the commercial algorithm was 36% more successful in reduction of variations due to metal artifact. Conclusion: The proposed approach can be applied successfully for dental filling artifact reduction in head and neck patients. Although the performance of the commercial method was superior to ours in near dental regions, for the farther regions with more critical organs was vice versa. However, weighting the interpolation and adaptive filtering steps may result in even better results.

192. Evaluation of a commercial orthopedic metal artefact reduction tool in radiation therapy

Purpose In radiotherapy process image artifacts can lead either a wrong definition of structure contours by the clinician either an erroneous computation of dose due to inaccuracies in the Hounsfield Unit (HU) values. Radiotherapy patients have often metal implants and this causes several image artifacts. This study is focused on the advantages using a commercial metal artifacts reduction algorithm, O-MAR (Philips Healthcare System, Cleveland, OH). Methods and materials The study is performed on five head and neck cases with metal dental implants. Patients were scanned on a large bore CT Brilliance Philips. The scanned images were reconstructed with standard and O-MAR algorithm for each patient. The structures drawing by the clinicians on the O-MAR series were copied, on the originally CT images to evaluate the dose distribution on the same volume. The plans have been made on Pinnacle TPS in nine field steep and shoot intensity modulated radiation therapy (IMRT). The treatment provided two or three PTVs, respectively with 54/66 Gy and 54/60/66 Gy and constraints were evaluated on different OARs, close to the artifacts region, such as bone marrow, parotids, mandibule. Hounsfield Units (HU) variation were analyzed also in additional region of interest (ROI) near the dental implant. Results In the OMAR images, noise values were generally reduced, standard deviation of HU is lower than standard images. Statistical analysis on HU values was performed, but without significant difference between the two data sets. Evaluating the dose distribution and the dose volume histogram (DVH) with the clinicians, no significant difference were detected. Conclusion In head and neck case, when patients have dental implants, the use of O-MAR improve the entire radiation treatment planning process, especially for contouring because increase the accuracy of CT HU and reduce the noise. No significant changes in dose calculation had been found.

Metal artifact reduction on cervical CT images by deep residual learning

BackgroundCervical cancer is the fifth most common cancer among women, which is the third leading cause of cancer death in women worldwide. Brachytherapy is the most effective treatment for cervical cancer. For brachytherapy, computed tomography (CT) imaging is necessary since it conveys tissue density information which can be used for dose planning. However, the metal artifacts caused by brachytherapy applicators remain a challenge for the automatic processing of image data for image-guided procedures or accurate dose calculations. Therefore, developing an effective metal artifact reduction (MAR) algorithm in cervical CT images is of high demand.MethodsA novel residual learning method based on convolutional neural network (RL-ARCNN) is proposed to reduce metal artifacts in cervical CT images. For MAR, a dataset is generated by simulating various metal artifacts in the first step, which will be applied to train the CNN. This dataset includes artifact-insert, artifact-free, and artifact-residual images. Numerous image patches are extracted from the dataset for training on deep residual learning artifact reduction based on CNN (RL-ARCNN). Afterwards, the trained model can be used for MAR on cervical CT images.ResultsThe proposed method provides a good MAR result with a PSNR of 38.09 on the test set of simulated artifact images. The PSNR of residual learning (38.09) is higher than that of ordinary learning (37.79) which shows that CNN-based residual images achieve favorable artifact reduction. Moreover, for a 512 × 512 image, the average removal artifact time is less than 1 s.ConclusionsThe RL-ARCNN indicates that residual learning of CNN remarkably reduces metal artifacts and improves critical structure visualization and confidence of radiation oncologists in target delineation. Metal artifacts are eliminated efficiently free of sinogram data and complicated post-processing procedure.

Impact of Single-Energy Metal Artifact Reduction on CT image quality in patients with dental hardware

BackgroundTo evaluate whether Canon's Single-Energy Metal Artifact Reduction (SEMAR) algorithm can significantly improve subjective and objective image quality of patients with nonremovable dental hardware undergoing CT imaging of the oral cavity and oropharynx. Materials and methodsSEMAR was reconstructed from routine Adaptive Iterative Dose Reduction (AIDR) images in 154 patients (46 females and 108 males; mean age 66.3 ± 10.5 years). Subjective SEMAR and AIDR image quality of the mouth floor, sublingual glands, lymphatic ring and overall impression were evaluated by two independent radiologists on a 6-point scale (1 = very good image quality, 6 = poor image quality) and compared to ratings of an oral and maxillofacial surgeon. Interrater agreement was assessed using the intraclass correlation coefficient (ICC). Objective image analysis was performed by placing regions of interest (ROIs) on the mouth floor and measuring CT attenuation in Hounsfield units (HU) and standard deviation (SD). ResultsSEMAR significantly improved subjective image quality in all evaluated structures for all raters (p < 0.001). Furthermore, SEMAR significantly reduced objective metal artifacts and image noise (p < 0.001). ConclusionSEMAR significantly improved diagnostic quality of CT images of the oral cavity and oropharynx by reducing artifacts caused by dental hardware.

Comparison of Metal Artifact Reduction in Dual- and Single-Source CT: A Vertebral Phantom Study.

The objective of this study was to compare the capability of two algorithms for metal artifact reduction and virtual monoenergetic imaging (VME), a metal artifact reduction application for dual-source CT. A bovine vertebra phantom with 16 artificial osteolyses and two 20 × 4.5 mm stainless steel screws was scanned on two single-source CT scanner and one dual-source CT scanner at a dose identical to the single-source acquisitions. Datasets were reconstructed with a metal artifact reduction algorithm for orthopedic implants (O-MAR, Philips Healthcare), an iterative metal artifact reduction algorithm (iMAR, Siemens Healthineers), and VME. Blinded to the method used for artifact reduction, three independent observers evaluated datasets regarding the extent of metal artifacts using a 4-point scale. Depicted osteolyses were counted and screw diameters measured for each reconstruction. Interobserver variability was evaluated using the Kendall coefficient of concordance for ordinal variables and the intraclass correlation coefficient for continuous data. VME showed the best metal artifact reduction capability among evaluated methods; overall artifacts were rated 1.08 ± 0.29 for VME, 3.33 ± 0.65 for iMAR, and 3.91 ± 0.29 for O-MAR (p < 0.01). VME resulted in better representation of the cortical bone, trabecular structure, and soft tissue compared with the other two algorithms. VME provided the most realistic reconstruction of screw diameter. However, VME missed osteolyses. Good to almost perfect agreement was achieved for nearly all evaluated attributes. In our vertebral phantom, VME led to the most detailed representation of the osteosynthesis screw, caused the lowest amount of artifact, and represented the adjacent tissue best. Thus, VME should be considered as an alternative method to evaluate implants when other algorithms fail.

Subtraction CTA: An Alternative Imaging Option for the Follow-Up of Flow-Diverter-Treated Aneurysms?

This was a pilot study to explore the diagnostic accuracy and safety of subtraction CTA combined with a single-energy metal artifact reduction algorithm (SEMAR) compared to DSA for the evaluation of intracranial aneurysm occlusion after flow diverter treatment. We included patients treated with a flow diverter for an unruptured intracranial aneurysm between November 2015 and November 2016. The patient cohort comprised 2 groups: those who underwent follow-up imaging 1 month after flow-diverter treatment and those with a known residual intracranial aneurysm after flow diverter treatment who underwent imaging at regular follow-ups. Full-brain subtraction CTA was performed on a 320-detector row CT system. A low-dose non-enhanced volume acquisition was followed by a contrast-enhanced volume CTA. Iterative and noise-reduction filters, SEMAR, and SURESubtraction algorithms were applied. DSA was performed on a flat panel C-arm angiography system. Standard posteroanterior, lateral, 3D, and detailed 2D acquisitions were performed. Imaging was independently scored by 2 clinicians. Aneurysm occlusion (Raymond scale) was our primary outcome parameter. Thirteen intracranial aneurysms were evaluated with subtraction CTA and DSA. Nine aneurysm remnants were demonstrated by both subtraction CTA and DSA. The sensitivity and specificity of subtraction CTA for the detection of aneurysm occlusion were 100% (95% CI, 82.41%-100%) and 100% (95% CI, 67.55%-100%), respectively. Agreement between readers was perfect (κ = 1.0). The smallest neck remnant detected on subtraction CTA was 1.2 mm. No complications occurred. Subtraction CTA with single-electron metal artifact reduction is effective in the reduction of metal artifacts of flow diverters and might therefore be a viable alternative in the assessment of intracranial aneurysm occlusion after flow diverter treatment.

Study on the usefulness of Metal artifact reduction algorithm and MonoE reconstruction (Dual Layer Detector) overlapping application

Study on the usefulness of Metal artifact reduction algorithm and MonoE reconstruction (Dual Layer Detector) overlapping application

Wavelet transform based on Meyer algorithm for image edge and blocking artifact reduction

In this study, a wavelet transform based on Meyer algorithm with edge-angle tracking capability is proposed for edge and blocking artifact reduction of an image, during image compression processes. This new proposed scheme is quite different from the conventional curvelet scheme, which can be viewed as using post-processing, after wavelet transform, to track only the edge of a high-frequency section of wavelet coefficients. However, the proposed wavelet transform scheme based on Meyer algorithm is with a complete wavelet design procedure, which is suitable for multiresolution analysis; it possesses the orthonormal property of conventional wavelet transforms. From computer simulation, we verify the merits of the proposed scheme over the conventional approaches, in terms of achieving better performance based on the subjective and objective (e.g., the peak signal-to-noise ratio) analysis.

The performance of metal artifact reduction algorithms in cone beam computed tomography images considering the effects of materials, metal positions, and fields of view

The aim of this study was to assess the performance of 2 metal artifact reduction (MAR) algorithms in cone beam computed tomography (CBCT) imaging, considering different materials, metal positions, and fields of view (FOVs). Nine phantoms containing cylinders of amalgam, copper-aluminum (Cu-Al) alloy, and titanium were scanned by using Picasso Trio and ProMax 3D CBCT units with small and medium FOVs. Scans were made with and without MAR algorithms. The standard deviation (SD) of voxel gray values was measured in the neighborhood of the cylinders. Differences in SD were statistically evaluated for effects of MAR and the other parameters, with a significance level of 5%. Significant differences between images with MAR and those without MAR for both devices (P ≤ .0001) were observed. Amalgam showed the largest artifact expression, followed by Cu-Al and titanium. After correction, differences remained only in Picasso Trio images (P = .002). Considering positions, no significant difference in the performance of the MAR algorithm was observed in either device. Considering FOVs, significant differences were observed for ProMax 3D (P = .005), with less artifact expression in the medium FOV after MAR correction. MAR algorithms were effective for artifact reduction despite variation in performance according to device, FOV, and material properties. The position of the metal cylinder within the FOV had no significant effect.

Single-energy metal artifact reduction technique for reducing metallic coil artifacts on post-interventional cerebral CT and CT angiography.

To evaluate the effects of the single-energy metal artifact reduction (SEMAR) algorithm on image quality of cerebral CT and CT angiography (CTA) for patients who underwent intracranial aneurysm coiling. Twenty patients underwent cerebral CT and CTA using a 320-detector row CT after intracranial aneurysm coiling. Images with and without application of the SEMAR algorithm (SEMAR CT and standard CT images, respectively) were reconstructed for each patient. The images were qualitatively assessed by two independent radiologists in a blinded manner for the depiction of anatomical structures around the coil, delineation of the arteries around the coil, and the depiction of the status of coiled aneurysms. Artifact strength was quantitatively assessed by measuring the standard deviation of attenuation values around the coil. The strength of artifacts measured in SEMAR CT images was significantly lower than that in standard CT images (25.7 ± 10.2 H.U. vs. 80.4 ± 67.2 H.U., p < 0.01, Student's paired t test). SEMAR CT images were significantly improved compared with standard CT images in the depiction of anatomical structures around the coil (p < 0.01, the sign test), delineation of the arteries around the coil (p < 0.01), and the depiction of the status of coiled aneurysms (p < 0.01). The SEMAR algorithm significantly reduces metal artifacts from intracranial aneurysm coiling and improves visualization of anatomical structures and arteries around the coil, and depiction of the status of coiled aneurysms on post-interventional cerebral CT.

Combined application of virtual monoenergetic high keV images and the orthopedic metal artifact reduction algorithm (O-MAR): effect on image quality

To determine whether there is any additional metal artifact reduction when virtual monochromatic images (VMI) and metal artifact reduction for orthopedic implants (O-MAR) are applied together compared to their separate application in both phantom and clinical abdominopelvic CT studies. An agar phantom containing a spinal prosthesis was scanned using a dual-layer, energy CT scanner (IQon, Philips Healthcare), and reconstructed with the filtered back-projection algorithm without O-MAR (FBP), filtered back-projection algorithm with O-MAR (O-MAR), VMI140 without O-MAR (VMI140), and VMI140 with O-MAR (VMI140 + O-MAR). Abdominopelvic CT images of 47 patients with metallic prostheses were also reconstructed in the same manner for clinical study. Noise measured as the standard deviation of CT Hounsfield units was compared between the four reconstruction methods in both phantom and clinical studies. Improvements in metal artifact reduction, image quality, and diagnostic improvement were further analyzed in the clinical study. Noise was significantly decreased when both VMI and O-MAR were applied in conjunction compared to their separate application in both phantom (16.3 HU vs. 25.0 and 26.4 HU) and clinical studies (15.8 HU vs. 19.2 and 26.2 HU). In the clinical study, the qualitative degree of artifacts was also significantly reduced with VMI140 + O-MAR (2.85 and 2.87) compared to VMI140 (2.36 and 2.26) or O-MAR (2.13 and 2.04) alone for both reviewers (P < 0.001) and improvements in image quality were observed in all 47 patients, with actual diagnostic improvements observed in three. Metal artifacts can be additionally reduced by applying O-MAR and VMI in conjunction, compared to their separate application, thereby improving diagnostic performance.

Development of a novel algorithm for metal artifact reduction in digital tomosynthesis using projection-based dual-energy material decomposition for arthroplasty: A phantom study

In this study, a novel dual-energy (DE) material decomposition reconstruction algorithm (DEMDRA) was developed using projection data with the aim of reducing metal artifacts during digital tomosynthesis (DT) for implants. Using the three-material decomposition method and decomposition projection data specific for each material, a novel DEMDRA was implemented to reduce metal artifacts via weighted hybrid reconstructed images [maximum likelihood expectation maximization (MLEM) and shift-and-add (SAA)]. Pulsed X-ray exposures with rapid switching between low and high tube potential kVp were used for DE-DT imaging, and the images were compared using conventional filtered back projection (FBP), MLEM, the simultaneous algebraic reconstruction technique total variation (SART-TV), virtual monochromatic processing, and metal artifact reduction (MAR)-processing algorithms. The reductions in metal artifacts were compared using an artifact index (AI), Gumbel distribution of the largest variations, and the artifact spread functions (ASFs) for prosthesis phantom. The novel DEMDRA yielded an adequately effective overall performance in terms of the AI, and the resulting images yielded good results independently of the type of metal used in the prosthetic phantom, as well as good noise artifact removal, particularly at greater distances from metal objects. Furthermore, the DEMDRA represented the minimum in the model of largest variations. Regarding the ASF analysis, the novel DEMDRA yielded superior metal artifact reduction when compared with conventional reconstruction algorithms with and without MAR processing. Finally, the DEMDRA was particularly useful for reducing high-frequency artifacts.

P276] Impact on proton range estimates using a novel mr-based artifact reduction algorithm

Purpose Metal implants lead to streak and cupping artifacts in computed tomography (CT) images, causing erroneous CT number estimates for radiation therapy (RT) planning. We recently introduced kerMAR, a novel Magnetic Resonance (MR)-based CT metal artifact reduction algorithm that combines kernel regression on uncorrupted CT value/MR patch pairs with a forward model of the CT metal artifacts. Here, we compare the impact of kerMAR and the clinical oMAR algorithm (Philips) on the proton range in calculated spot scanning (SS) dose plans for proton RT. Methods We acquired T1w MR and CT image sets of a veal shank phantom with and without metal markers inserted, and applied kerMAR and oMAR to the former. We then created SS plans in Eclipse v. 13.7 (Varian) delivering 150 MeV protons in a 0.55 cm single spot that passed 1) near a metal marker at shallow depth and 2) near two different markers located at shallow (near bone) and deep depths, respectively. Similar images were acquired for 4 head-and-neck (HN) RT patients with dental implants, and plans using the same phantom beam, angled through the artifact corrupted oral cavity, were devised, leading to a configuration most resembling phantom beam 2. We finally recalculated the dose plans for the same beamline settings and monitor units on all CT sets, and compared the proton ranges defined as the depth with 80% of the maximum dose. Results For the phantom plans, the following range deviations relative to the metal-free reference plan (uncorrected CT, oMAR, kerMAR) were observed: Plan 1: (0.6, 0.6, 0.6)%; plan 2: (−4, −1.8, −2.1)%. The patient plans showed the following deviations from the uncorrected CT plan: kerMAR: (10, 8, −7, 11)%; oMAR: (3, 0.1, −10, 0.2)%. Conclusions Proton range calculations on a phantom showed similar improvements compared to the uncorrupted reference with kerMAR and oMAR. Similar calculations on HN patients, however, displayed systematic proton range increases when applying kerMAR as compared to oMAR.

Iterative algorithms for metal artifact reduction in children with orthopedic prostheses: preliminary results.

Increased computational power allows computed tomography (CT) software to process very advanced mathematical algorithms to generate better quality images at lower doses. One such algorithm, iterative metal artifact reduction (iMAR) has proven to decrease metal artifacts seen in CT images of adults with orthopedic implants. To evaluate artifact reduction capability of the algorithm in lower-dose pediatric CT compared to our routine third-generation advanced modeled iterative reconstruction (ADMIRE) algorithm. Thirteen children (11-17years old) with metal implants underwent routine clinically indicated CT. Data sets were reconstructed with an iMAR algorithm. Hounsfield units and image noise were measured in bone, muscle and fat in the streak artifact (near the implant) and at the greatest distance from the artifact (far from the implant). A regression model compared the effects of the algorithm (standard ADMIRE vs. iMAR) near and far from the implant. Near the implant, Hounsfield units with iMAR were significantly different in our standard ADMIRE vs. iMAR for bone, muscle and fat (P<0.001). Noise was significantly different in standard ADMIRE vs. iMAR in bone (P<0.003). Far from the implant, Hounsfield units and noise were not significantly different for ADMIRE vs. iMAR, for the three tissue types. These preliminary results demonstrate that iMAR algorithms improves Hounsfield units near the implant and decreases image noise in bone in low-dose pediatric CT. It does this without changing baseline tissue density or noise far from the implant.

BLOCK ARTIFACT REDUCTION USING BINARY EDGE RETAINING MAPS

in this paper we propose a new edge-retaining algorithm for block artifact reduction. We have classified the pixels to categorize every pixel into one amongst two categories, particularly edge region and smooth region and then Edge-Retaining maps are used to describe these regions. Finally, A Two-step adaptive filter, based on these maps and incorporating offset filtering and edge retaining filtering is used for removing the block artifacts. Experimental Results prove that our proposed edge retaining algorithm adequately reduces block artifacts while conserving the details and the Peak to Signal Noise Ratio (PSNR) performance is better than that of various previous algorithms which use block classification.