• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.2
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• pp.21-26
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• 2016

Purpose Because of many advantages, PET-CT Scanners generally use CT Data for attenuation correction. By using CT based attenuation correction, we can get anatomical information, reduce scan time and make more accurate correction of attenuation. However in case metal artifact occurred during CT scan, CT-based attenuation correction can induce artifacts and quantitative errors that can affect the PET images. Therefore this study infers true SUV of metal artifact region from attenuation corrected image count -to- non attenuation corrected image count ratio. Materials and Methods Micro phantom inserted $^{18}F-FDG$ 4mCi was used for phantom test and Biograph mCT S(40) is used for medical test equipment. We generated metal artifact in micro phantom by using metal. Then we acquired both metal artifact region of correction factor and non metal artifact region of correction factor by using attenuation correction image count -to- non attenuation correction image count ratio. In case of clinical image, we reconstructed both attenuation corrected images and non attenuation corrected images of 10 normal patient($66{\pm}15age$) who examined PET-CT scan in SNUH. After that, we standardize several organs of correction factor by using attenuation corrected image count -to- non attenuation corrected count ratio. Then we figured out metal artifact region of correction factor by using metal artifact region of attenuation corrected image count -to- non attenuation corrected count ratio And we compared standard organs correction factor with metal artifact region correction factor. Results according to phantom test results, metal artifact induce overestimation of correction factor so metal artifact region of correction factors are 12% bigger than the non metal artifact region of correction factors. in case of clinical test, correction factor of organs with high CT number(>1000) is $8{\pm}0.5%$, correction factor of organs with CT number similar to soft tissue is $6{\pm}2%$ and correction factor of organs with low CT number(-100>) is $3{\pm}1%$. Also metal artifact correction factors are 20% bigger than soft tissue correction factors which didn't happened metal artifact. Conclusion metal artifact lead to overestimation of attenuation coefficient. because of that, SUV of metal artifact region is overestimated. Thus for more accurate quantitative evaluation, using attenuation correction image count -to-non attenuation correction image count ratio is one of the methods to reduce metal artifact affect.

• The Journal of Korean Society for Radiation Therapy
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• v.22 no.2
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• pp.85-95
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• 2010

Purpose: The degradation of an image quality and error of the beam dose calculation can be caused because the metal artifact is generated during the CT simulation of head and neck patient. The usability of the gantry tilt scan for reducing the metal artifact tries to be appraised. Materials and Methods: The inferior $20^{\circ}$ gantry tilt scan was made in order to reduce the metal artifact and $0^{\circ}$ reconstruction image was acquired. The AAPM CT performance Phantom was used in order to compare the CT number of the reconstructed image and Original image. the difference of volume was compared by using the acrylic phantom. The homogeneity of the CT number was evaluated the Intensity volume Histogram (IVH) as in order to evaluate an influence by the metal artifact. A dose was evaluated as the Dose Volume Histogram (DVH). Results: in the comparison of the CT number and volume, the difference showed up less than 0.5%. As to the comparison of IVH, in the gantry tilt scan, influence by an artifact was reduced and the homogeneity of the CT number was improved. The comparison of DVH result reduced the mean dose error of the both sides parotid 0.2~6%. Conclusion: In the Head & Neck radiation therapy, It is difficult and to distinguish tumor and normal tissue and the error of dose is generated by the metal artifact. The delineation of the exact organization was possible if the Gantry tilt scan was used. The CT number homogeneity was improved and the error of dose could be reduced. The Gantry tilt scan confirmed in the Head & Neck radiation therapy to be very useful in the exact radiation therapy.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.1
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• pp.107-114
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• 2014

Purpose : The purpose of this study is evaluation for the applicability of O-MAR(Metal artifact Reduction for Orthopedic Implants)(ver. 3.6.0, Philips, Netherlands) in head & neck radiation treatment planning CT with metal artifact created by dental implant. Materials and Methods : All of the in this study's CT images were scanned by Brilliance Big Bore CT(Philips, Netherlands) at 120kVp, 2mm sliced and Metal artifact reduced by O-MAR. To compare the original and reconstructed CT images worked on RTPS(Eclipse ver 10.0.42, Varian, USA). In order to test the basic performance of the O-MAR, The phantom was made to create metal artifact by dental implant and other phantoms used for without artifact images. To measure a difference of HU in with artifact images and without artifact images, homogeneous phantom and inhomogeneous phantoms were used with cerrobend rods. Each of images were compared a difference of HU in ROIs. And also, 1 case of patient's original CT image applied O-MAR and density corrected CT were evaluated for dose distributions with SNC Patient(Sun Nuclear Co., USA). Results : In cases of head&neck phantom, the difference of dose distibution is appeared 99.8% gamma passing rate(criteria 2 mm / 2%) between original and CT images applied O-MAR. And 98.5% appeared in patient case, among original CT, O-MAR and density corrected CT. The difference of total dose distribution is less than 2% that appeared both phantom and patient case study. Though the dose deviations are little, there are still matters to discuss that the dose deviations are concentrated so locally. In this study, The quality of all images applied O-MAR was improved. Unexpectedly, Increase of max. HU was founded in air cavity of the O-MAR images compare to cavity of the original images and wrong corrections were appeared, too. Conclusion : The result of study assuming restrained case of O-MAR adapted to near skin and low density area, it appeared image distortion and artifact correction simultaneously. In O-MAR CT, air cavity area even turned tissue HU by wrong correction was founded, too. Consequentially, It seems O-MAR algorithm is not perfect to distinguish air cavity and photon starvation artifact. Nevertheless, the differences of HU and dose distribution are not a huge that is not suitable for clinical use. And there are more advantages in clinic for improved quality of CT images and DRRs, precision of contouring OARs or tumors and correcting artifact area. So original and O-MAR CT must be used together in clinic for more accurate treatment plan.

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.227-232
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• 2019

MRI examination for patients with metal objects has in poor image quality. Metallic implants can result in poor image because magnetic susceptibility causes signal loss and distortion and makes poor imaging, which is called magnetic susceptibility artifact or metal artifact. There are several approaches to reduce metal artifacts. In this study, we study the reduction of metal artifact by VAT and SEMAC techniques. A metal implant used for orthopedic surgery was attached to the phatom and the distortion caused by the artifact was measured under T1WI and T2WI protocols. Several techniques of VAT only and VAT and SEMAC for the reduction of metal artifact were compared. The metal artifact showed a reduction of at least 8% to a maximum of 26% in the VAT-SEMAC. The VAT-SEMAC technique can be applied to patients with orthopedic implants to improve image quality. If scan time and image quality are simultaneously considered in VAT-SEMAC technique, metal artifact will be reduced in clinical practice.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.2854-2863
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• 2023

Objective: To present a hybrid approach that incorporates a constrained beam-hardening estimator (CBHE) and deep learning (DL)-based post-refinement for metal artifact reduction in dental cone-beam computed tomography (CBCT). Methods: Constrained beam-hardening estimator (CBHE) is derived from a polychromatic X-ray attenuation model with respect to X-ray transmission length, which calculates associated parameters numerically. Deep-learning-based post-refinement with an artifact disentanglement network (ADN) is performed to mitigate the remaining dark shading regions around a metal. Artifact disentanglement network (ADN) supports an unsupervised learning approach, in which no paired CBCT images are required. The network consists of an encoder that separates artifacts and content and a decoder for the content. Additionally, ADN with data normalization replaces metal regions with values from bone or soft tissue regions. Finally, the metal regions obtained from the CBHE are blended into reconstructed images. The proposed approach is systematically assessed using a dental phantom with two types of metal objects for qualitative and quantitative comparisons. Results: The proposed hybrid scheme provides improved image quality in areas surrounding the metal while preserving native structures. Conclusion: This study may significantly improve the detection of areas of interest in many dentomaxillofacial applications.

• Imaging Science in Dentistry
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• v.48 no.1
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• pp.41-44
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• 2018

Purpose: To evaluate the effect of different numbers of basis images and the use of metal artifact reduction (MAR) on the production and reduction of artifacts in cone-beam computed tomography images. Materials and Methods: An acrylic resin phantom with a metal alloy sample was scanned, with 450 or 720 basis images and with or without MAR. Standard deviation values for the test areas (around the metal object) were obtained as a way of measuring artifact production. Two-way analysis of variance was used with a 5% significance level. Results: There was no significant difference in artifact production among the images obtained with different numbers of basis images without MAR (P=.985). MAR significantly reduced artifact production in the test areas only in the protocol using 720 basis images (P=.017). The protocol using 450 basis images with MAR showed no significant difference in artifact production when compared to the protocol using 720 basis images with MAR (P=.579). Conclusion: Protocols with a smaller number of basis images and with MAR activated are preferable for minimizing artifact production in tomographic images without exposing the patient to a greater radiation dose.

• The Journal of Korean Society for Radiation Therapy
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• v.29 no.1
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• pp.49-56
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• 2017

Purpose: To evaluate the accuracy of the Iterative Metal Artifact Reduction (IMAR) algorithm in correcting CT (computed tomography) images distorted due to a metal artifact and to evaluate the usefulness when proton therapy plan was plan using the images on which IMAR algorithm was applied. Materials and Methods: We used a CT simulator to capture the images when metal was not inserted in the CIRS model 062 Phantom and when metal was inserted in it and Artifact occurred. We compared the differences in the CT numbers from the images without metal, with a metal artifact, and with IMAR algorithm by setting ROI 1 and ROI 2 at the same position in the phantom. In addition, CT numbers of the tissue equivalents located near the metal were compared. For the evaluation of Rando Phantom, CT was taken by inserting a titanium rod into the spinal region of the Rando phantom modelling a patient who underwent spinal implant surgery. In addition, the same proton therapy plan was established for each image, and the differences in Range at three sites were compared. Results: In the evaluation of CIRS Phantom, the CT numbers were -6.5 HU at ROI 1 and -10.5 HU at ROI 2 in the absence of metal. In the presence of metal, Fe, Ti, and W were -148.1, -45.1 and -151.7 HU at ROI 1, respectively, and when the IMAR algorithm was applied, it increased to -0.9, -2.0, -1.9 HU. In the presence of metal, they were 171.8, 63.9 and 177.0 HU at ROI 2 and after the application of IMAR algorithm they decreased to 10.0 6,7 and 8.1 HU. The CT numbers of the tissue equivalents were corrected close to the original CT numbers except those in the lung located farthest. In the evaluation of the Rando Phantom, the mean CT numbers were 9.9, -202.8, and 35.1 HU at ROI 1, and 9.0, 107.1, and 29 HU at ROI 2 in the absence, presence of metal, and in the application of IMAR algorithm. The difference between the absence of metal and the range of proton beam in the therapy was reduced on the average by 0.26 cm at point 1, 0.20 cm at point 2, and 0.12 cm at point 3 when the IMAR algorithm was applied. Conclusion: By applying the IMAR algorithm, the CT numbers were corrected close to the original ones obtained in the absence of metal. In the beam profile of the proton therapy, the difference in Range after applying the IMAR algorithm was reduced by 0.01 to 3.6 mm. There were slight differences as compared to the images absence of metal but it was thought that the application of the IMAR algorithm could result in less error compared with the conventional therapy.

• Journal of radiological science and technology
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• v.43 no.2
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• pp.79-85
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• 2020

The influence of metal artifact in CT image depends on the type of metal materialsm, the reconstruction algorithm, and scan parameters. The presence of metal artifacts was quantitatively evaluated by applying the standard and MAR algorithms through the phantom study. In the change of tube voltage applied the standard algorithm, metal artifact decreased to 44.9% for 80 vs 120 kVp, 24% for 100 vs 120 kVp, while the image taken at 140 kVp increased the artifact by 19% compared to 120 kVp. When the tube current was increased from 100 to 300 mA, there was no significant difference in the CT value and noise. Black band and white strike artifacts occurred up to 65.9% in the adjacent ROI of the metal driver, whereas titanium screw produced lesser metal artifact than that of the metal driver. The combination of 120kVp or higher tube voltage-standard algorithm was effective in removing black band artifacts as well as white streak by high density materials. However, MAR reconstruction algorithm was useful in improving image quality under the environment of low kVp and high density materials, without increase of radiation exposure.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.279-280
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• 1998

A new algorithm is developed that can reduce the metal artifact on CT caused by pedicle screws. Metal artifact has been recognized as a major problem in precise reading of CT images. In particular, spine surgeons have been bothered with the artifact appearing on CT taken after pedicle screw insertion. To reduce the artifact, our new algorithm first finds the center line from CT images, and then overlays an exact size screw image on the CT. The exact screw is obtained from an actual design specifications of screw, and the CT images are processed to maximize bone margins while minimizing screw images through adjusting the window width and level. 실험 결과 단순한 Window W/L 조절로는 해결되지 않는군요. This algorithm provides spine surgeons with more accurate CT images and thus better interpretation of CT to ascertain the success or failure of pedicle screw insertion.

• Journal of Radiation Protection and Research
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• v.36 no.2
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• pp.79-85
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• 2011

OThe purpose of this article was to measure and compare the value of the metal artifact reduction (MAR) algorithm by Dual energy(kVp switching) CT (Computed Tomography) for non using MAR and we introduced new variable Dual energy CT applications through a clinical scan. The used equipment was GE Discovery 750HD with Dual-Energy system(kVp switching). CT scan was performed on the neck and abdomen area subject for patients. Studies were from Dec 20 2010 to Feb 10 2011 and included 25 subject patients with prosthesis. We were measured the HU (Hounsfield Unit) and noise value at metal artifact appear(focal loss of signal and white streak artifact area) according to the using MAR algorithm. Statistical analyses were performed using the paired sample t-test. In patient subject case, the statistical difference of showing HU was p=0.01 and p=0.04 respectively. At maximum black hole artifact area and white streak artifact area according to the using MAR algorithm. However noise was p=0.05 and p=0.04 respectively; and not the affected black hole and white streak artifact area. Dual Energy CT with the MAR algorithm technique is useful reduce metal artifacts and could improve the diagnostic value in the diagnostic image evaluation of metallic implants area.