• 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 Digital Convergence
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• v.10 no.2
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• pp.243-247
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• 2012

Beam hardening artifact happens in the CT image. when a PET/CT is conducted while there is a metallic dental implant. The artifact appears in the CT image can affect the PET image. When the patient with head and neck cancer has a metallic dental implant, Beam hardening artifact which was taken in th CT image can change the PET image and SUV value. Therefore, by Quantitative measure of the SUV according to the change in HU by the metallic dental implant, the appropriacy in the clinical application was assessed. The records of 47 patients with PET/CT August 2011. For the analysis, 2 region of interest were defined in area where CT and PET image. As a result of the experiment, if there in an implant, the HU and the SUV increased and there existed a statistically significant difference(p<0.01). Although this level of increase was not large compared with that in the patient who have no metallic dental implant, when a person has head and neck cancer, it is even more likely to be overestimated when diagnosing the cancer. When conducting PET/CT for the patient who have head and neck cancer, the physical biological parts should be considered in order not to make an error in decoding.

• Progress in Medical Physics
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• v.15 no.1
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• pp.23-29
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• 2004

The relationship between the dose calculated with a radiotherapy treatment planning system (RTPS) and CT number verses the relative electron density curve was investigated for various CT voltages and beam qualifies. We obtained the relationship between the CT numbers and electron densities of the tissue equivalent materials for various CT voltages and beam qualifies. At lower CT voltages, the higher density materials, like cortical bone, showed larger CT numbers and the soft tissues showed no variations. We peformed a phantom study in a RTPS, where a phantom consisted of lung and bone legions in water. We calculated the dose received behind the lung and bone regions for 6 MV photon beams, in which the regions below the lung, water and bone received higher doses in this listed order. The result was the same for 10 MV photon beams. For the clinical application, the doses were calculated for the lung and pelvis. No difference was observed when using different electron density conversion tables with various CT voltages from a same CT. A relative dose difference of 1.5% was obtained when the CT machine for the density conversion table was different from that for the CT image for planning.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.942-952
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• 2006

We propose an automatic segmentation method for identifying pulmonary structures using gray-level information of chest CT images. Our method consists of following five steps. First, to segment pulmonary structures based on the difference of gray-level value, we select the threshold using optimal thresholding. Second, we separate the thorax from the background air and then the lungs and airways from the thorax by applying the inverse operation of 2D region growing in chest CT images. To eliminate non-pulmonary structures which has similar intensities with the lungs, we use 3D connected component labeling. Third, we segment the trachea and left and right mainstem bronchi using 3D branch-based region growing in chest CT images. Fourth, we can obtain accurate lung boundaries by subtracting the result of third step from the result of second step. Finally, we select the threshold in accordance with histogram analysis and then segment radio-dense pulmonary vessels by applying gray-level thresholding to the result of the second step. To evaluate the accuracy of proposed method, we make a visual inspection of segmentation result of lungs, airways and pulmonary vessels. We compare the result of the conventional region growing with the result of proposed 3D branch-based region growing. Experimental results show that our proposed method extracts lung boundaries, airways, and pulmonary vessels automatically and accurately.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.717-723
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• 2023

Liver disease is highly associated with death, and other abdominal diseases are also important causes affecting a person's lifespan, and a CT scan is essential when treating abdominal diseases. High radiation exposure is essential to create images that are good for reading, but managing the patient's radiation exposure is also essential. In this study, a post-processing wavelet algorithm was proposed to improve the image quality of abdominal CT images. Wavelets have the disadvantage of having to set a threshold value depending on the type of input image. Therefore, we experimentally proposed the threshold value of the wavelet and evaluated whether the image quality was effective. As a result of the experiment, the optimal threshold value for abdominal CT images was calculated to be 50. In the case of image 1, noise was improved by 49% and in the case of image 2, by 29%, and the contrast also increased. if the results of this study are applied for post-processing after abdominal CT, image quality can be improved and it will be helpful in disease diagnosis.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.803-808
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• 2002

This paper describes automatic methods for detection of kidney and kidney tumor on abdominal CT scans. The abdominal CT images were digitalized using a film digitizer and a gray-level threshold method was used to segment the kidney. Based on texture analysis results, which were perform on sample images of kidney tumors, SEED region of kidney tumor was selected as result of homogeneity test. The average and standard deviation, which are representative statistical moments, were used to as an acceptance criteria for homogeneous test. Region growing method was used to segment the kidney tumor from the center pixel of selected SEED region using a gray-level value as an acceptance criteria for homogeneity test. These method were applied to 113 images of 9 cases, which were scanned by GE Hispeed Advantage CT scanner and digitalized by Lumisvs LS-40 film digitizer. The sensitivity was 85% and there was no false-positive results.

• Progress in Medical Physics
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• v.26 no.4
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• pp.229-233
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• 2015

We retrospectively reviewed lung cancer patients who were treated with stereotactic ablative radiotherapy (SABR). We investigated the value of response evaluation after treatment by measuring the volume change of tumors on serial chest computed tomography (CT) examinations. The study included 11 consecutive patients with early-stage (T1-T2aN0M0) non-small cell lung cancer (NSCLC) who were treated with SABR. The median dose of SABR was 6,000 cGy (range 5,000~6,400) in five fractions. Sequential follow-up was performed with chest CT scans. Median follow-up time was 28 months. Radiologic measurement was performed on 51 CT scans with a median of 3 CT scans per patient. The median time to partial response ($T_{PR}$) was 3 months and median time to complete remission ($T_{CR}$) was 5 months. Overall response rate was 90.9% (10/11). Five patients had complete remission, five had partial response, and one patient developed progressive disease without response. On follow-up, three patients (27.2%) developed progressive disease after treatment. We evaluated the the response after SABR. Our data also showed the timing of response after SABR.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.2
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• pp.21-25
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• 2010

Purpose: For better PET imaging with accuracy the transmission scanning is inevitably required for attenuation correction. The attenuation is affected by condition of acquisition and patient position, consequently quantitative accuracy may be decreased in emission scan imaging. In this paper, the present study aims at providing the measurement for attenuation varying with the positions of the patient's arm in whole body PET/CT, further performing the comparative analysis over its SUV changes. Materials and Methods: NEMA 1994 PET phantom was filled with $^{18}F$-FDG and the concentration ratio of insert cylinder and background water fit to 4:1. Phantom images were acquired through emission scanning for 4min after conducting transmission scanning by using CT. In an attempt to acquire image at the state that the arm of the patient was positioned at the lower of ahead, image was acquired in away that two pieces of Teflon inserts were used additionally by fixing phantoms at both sides of phantom. The acquired imaged at a were reconstructed by applying the iterative reconstruction method (iteration: 2, subset: 28) as well as attenuation correction using the CT, and then VOI was drawn on each image plane so as to measure CT number and SUV and comparatively analyze axial uniformity (A.U=Standard deviation/Average SUV) of PET images. Results: It was found from the above phantom test that, when comparing two cases of whether Teflon insert was fixed or removed, the CT number of cylinder increased from -5.76 HU to 0 HU, while SUV decreased from 24.64 to 24.29 and A.U from 0.064 to 0.052. And the CT number of background water was identified to increase from -6.14 HU to -0.43 HU, whereas SUV decreased from 6.3 to 5.6 and A.U also decreased from 0.12 to 0.10. In addition, as for the patient image, CT number was verified to increase from 53.09 HU to 58.31 HU and SUV decreased from 24.96 to 21.81 when the patient's arm was positioned over the head rather than when it was lowered. Conclusion: When arms up protocol was applied, the SUV of phantom and patient image was decreased by 1.4% and 9.2% respectively. With the present study it was concluded that in case of PET/CT scanning against the whole body of a patient the position of patient's arm was not so much significant. Especially, the scanning under the condition that the arm is raised over to the head gives rise to more probability that the patient is likely to move due to long scanning time that causes the increase of uptake of $^{18}F$-FDG of brown fat at the shoulder part together with increased pain imposing to the shoulder and discomfort to a patient. As regarding consideration all of such factors, it could be rationally drawn that PET/CT scanning could be made with the arm of the subject lowered.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.135-138
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• 2000

흉부 X선 CT 화상을 이용한 폐종류의 경계 형상을 정량적으로 평가하기 위하여 푸리에 변환된 폐종류 음영의 윤곽선 내 power spectrum 고주파 성분의 총합이 폐종류 음영의 경계 형상에 관한 유효한 평가 값이 되는지의 여부를 검토하였다. 이 평가 값은 폐종류 음영의 CT 화상 위의 특징을 명확히 반영한다고 판단된다. 다시 말해서, 윤곽선은 양성 혹은 악성 종류에 있어서 각각 명확하거나 불투명하다. 양성 IS명과 악성 16명인 환자 31명에 대해서 이 평가 값을 계산하여 통계적 처리를 행한 결과 양성과 악성 간에 뚜렷한 차이를 인식할 수 있었다. 이러한 제안된 평가 방법에 의해, power spectrum 고주파 성분의 총합이 폐종류 경계 형상의 평가치가 되어, 정량적인 폐종류의 양성과 악성 감별을 행할 때 유용한 값이 될 가능성을 시사한다고 볼 수 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.526-528
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• 2002

본 논문은 CT 영상을 이용하여 체지방과 근육의 체적 및 비율을 분석하는 알고리즘 개발에 대하여 기술한다. CT 영상에는 체지방, 근육, 공기, 뼈등의 구성성분들이 서로 다른 명암값을 가지고 분포한다. 이 논문에서는 히스토그램을 통하여 각 구성성분에 대한 명암값을 찾아내었다. 찾아낸 명암값에 따라 체지방과 근육 그리고 뼈, 공기에 각각 색을 입혀 시각적으로 표현하여 체지방과 근육의 분포와 비율을 볼 수 있는 환경을 만들고 수치적으로 체적 및 비율의 결과 값을 출력하는 알고리즘을 개발하였다. 또한 단계적인 체지방 측정 프로그램을 위해 DB 환경을 구축하여 모든 자료를 저장하고 불러올 수 있는 환경을 만들어 체지방 측정 알고리즘을 완성하였다. 알고리즘은 돼지 실험에서 측정된 체지방과 비교하여 정확성을 검증한 결과 약 92.86%의 정확도를 보였다.