• Journal of Radiation Protection and Research
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• v.33 no.2
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• pp.47-51
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• 2008

Objective: This study analyzed errors due to rotation or tilt of the magnetic resonance (MR) imaging indicator during image acquisition for a stereotactic radiosurgery. The error correction procedure of a commercially available stereotactic neurosurgery treatment planning program has been verified. Materials and Methods: Software virtual phantoms were built with stereotactic images generated by a commercial programming language, Interactive Data Language (version 5.5). The thickness of an image slice was 0.5 mm, pixel size was $0.5{\times}0.5mm$, field of view was 256 mm, and image resolution was $512{\times}512$. The images were generated under the DICOM 3.0 standard in order to be used with Leksell GammaPlan$^{(R)}$. For the verification of the rotation error correction function of Leksell GammaPlan$^{(R)}$, 45 measurement points were arranged in five axial planes. On each axial plane, there were nine measurement points along a square of length 100 mm. The center of the square was located on the z-axis and a measurement point was on the z-axis, too. Five axial planes were placed at z=-50.0, -30.0, 0.0, 30.0, 50.0 mm, respectively. The virtual phantom was rotated by $3^{\circ}$ around one of x, y, and z-axis. It was also rotated by $3^{\circ}$ around two axes of x, y, and z-axis, and rotated by $3^{\circ}$ along all three axes. The errors in the position of rotated measurement points were measured with Leksell GammaPlan$^{(R)}$ and the correction function was verified. Results: The image registration errors of the virtual phantom images was $0.1{\pm}0.1mm$ and it was within the requirement of stereotactic images. The maximum theoretical errors in position of measurement points were 2.6 mm for a rotation around one axis, 3.7 mm for a rotation around two axes, and 4.5 mm for a rotation around three axes. The measured errors in position was $0.1{\pm}0.1mm$ for a rotation around single axis, $0.2{\pm}0.2mm$ for double and triple axes. These small errors verified that the rotation error correction function of Leksell GammaPlan$^{(R)}$ is working fine. Conclusion: A virtual phantom was built to verify software functions of stereotactic neurosurgery treatment planning program. The error correction function of a commercial treatment planning program worked within nominal error range. The virtual phantom of this study can be applied in many other fields to verify various functions of treatment planning programs.

• The Korean Journal of Nuclear Medicine Technology
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• v.22 no.1
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• pp.55-66
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• 2018

Purpose In PET/CT exam, washed-out artifact could occur due to severe motion of the patient and high specific activity, it results in lowering not only qualitative reading but also quantitative analysis. Scatter limitation correction by GE is an algorism to correct washed-out artifact and recover the images in PET scan. The purpose of this study is to measure the threshold of specific activity which can recovers to original uptake values on the image shown with washed-out artifact from phantom experiment and to compare the quantitative analysis of the clinical patient's data before and after correction. Materials and Methods PET and CT images were acquired in having no misalignment(D0) and in 1, 2, 3, 4 cm distance of misalignment(D1, D2, D3, D4) respectively, with 20 steps of each specific activity from 20 to 20,000 kBq/ml on $^{68}Ge$ cylinder phantom. Also, we measured the distance of misalignment of foley catheter line between CT and PET images, the specific activity which makes washed-out artifact, $SUV_{mean}$ of muscle in artifact slice and $SUV_{max}$ of lesion in artifact slice and $SUV_{max}$ of the other lesion out of artifact slice before and after correction respectively from 34 patients who underwent $^{18}F-FDG$ Fusion Whole Body PET/CT exam. SPSS 21 was used to analyze the difference in the SUV between before and after scatter limitation correction by paired t-test. Results In phantom experiment, $SUV_{mean}$ of $^{68}Ge$ cylinder decreased as specific activity of $^{18}F$ increased. $SUV_{mean}$ more and more decreased as the distance of misalignment between CT and PET more increased. On the other hand, the effect of correction increased as the distance more increased. From phantom experiments, there was no washed-out artifact below 50 kBq/ml and $SUV_{mean}$ was same from origin. On D0 and D1, $SUV_{mean}$ recovered to origin(0.95) below 120 kBq/ml when applying scatter limitation correction. On D2 and D3, $SUV_{mean}$ recovered to origin below 100 kBq/ml. On D4, $SUV_{mean}$ recovered to origin below 80 kBq/ml. From 34 clinical patient's data, the average distance of misalignment was 2.02 cm and the average specific activity which makes washed-out artifact was 490.15 kBq/ml. The average $SUV_{mean}$ of muscles and the average $SUV_{max}$ of lesions in artifact slice before and after the correction show a significant difference according to a paired t-test respectively(t=-13.805, p=0.000)(t=-2.851, p=0.012), but the average $SUV_{max}$ of lesions out of artifact slice show a no significant difference (t=-1.173, p=0.250). Conclusion Scatter limitation correction algorism by GE PET/CT scanner helps to correct washed-out artifact from motion of a patient or high specific activity and to recover the PET images. When we read the image occurred with washed-out artifact by measuring the distance of misalignment between CT and PET image, specific activity after applying scatter limitation algorism, we can analyze the images more accurately without repeating scan.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.21 no.3
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• pp.269-275
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• 2003

The cadastral system which accomplishes the base of national land administration with accuracy of proper data and the cadastral maintenance quickly is agreeing with the actual place in information ages in Inundation. But even in spite of many efforts, various Problems are exposed in accuracy of the data on the cadastral maps and local situation must agree accurately from the process which propels cadastral information systems. Therefore, it must be carried out the cadastral non correspondence arrangement first of all in link of the plan which it corrects the error of existing data and computerization quickly. It summarizes the research as follows ; Cadastral non correspondence of the land boundaries on the map and actual circumstance does not agree with cadastral maps accurately, The lands which exceed the standards with the position error excess of 50cm on lil ,200 and 240cm on 1/6,000 areas on the map scale are the registration correction objectives. It is investigated that the cadastral non correspondence parcels occur in various cause and long period, the area error corrections are mainly objectives, and about 80% of the test area comes to reveal within permitted the limit of the measurement of planimetric area for cadastral survey, so it is not difficult with the fact that the compensation back which it follows in area increase and decrease and the location error correction becomes the important object fer the cadastral non correspondence arrangement projects.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.116-124
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• 2008

This study presents the application of multi-temporal and multi-scale panchromatic aerial photos for change detection in a small urban area. For aerial photos of the scale of 1:20,000 taken in 1987 and 1996 and the scale of 1:37,500 taken in 2000. Pre-processing that make the same conditions to all of the aerial photos was carried out through geometric correction, registration, contrasting, resamplimg, and mosaicking and then change detection were carried out respectively by image differencing and image ratio techniques. As a result, the change of urban features and landcover were able to be detected from panchromatic aerial photos that is single-band images and then the detected change results were compared between both techniques.

• The Journal of Advanced Prosthodontics
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• v.12 no.3
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• pp.107-113
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• 2020

PURPOSE. The aim of this study was to examine the importance of the defect-free scanning of a scan body by assessing the accuracy of virtual implant positioning in computer-aided design (CAD) software when the scan body image is improperly scanned. MATERIALS AND METHODS. A scan body was digitized in a dentiform model using an intraoral scanner, and scanned images with differing levels of image deficiency were generated: 5%, 10%, and 15% deficiency in the flat or rounded area. Using a best-fit image matching algorithm on each of the deficient scan body images, corresponding virtual implants were created. The accuracy of the implant position was evaluated by comparing the linear and angular discrepancies between the actual and virtual positions of the implant. Kruskal-Wallis tests and Mann-Whitney U tests with Bonferroni correction were used to determine the statistical differences among the seven scanned image deficiency groups (α=.05). RESULTS. In general, the linear and angular discrepancies of the implant position in the software increased as the deficiency of the scan body images increased. A 15% scan body image deficiency generated larger discrepancies than deficiency of 5% and 10%. The difference of scan defect position, flat or rounded area, did not affect the accuracy of virtual implant orientation at 5% and 10% deficiency level, but did affect the accuracy at 15% deficiency level. CONCLUSION. Deficiencies in the scanned images of a scan body can decrease the accuracy of the implant positioning in CAD software when the defect is large, thus leading to the incorrect fabrication of implant prostheses.

• Investigative Magnetic Resonance Imaging
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• v.19 no.3
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• pp.168-177
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• 2015

Purpose: Brain surface intensity model (BSIM)-based cortical thickness analysis does not require complicated 3D segmentation of brain gray/white matters. Instead, this technique uses the local intensity profile to compute cortical thickness. The aim of the present study was to evaluate intra-rater and inter-rater reliability of BSIM-based cortical thickness analysis using images from elderly participants. Materials and Methods: Fifteen healthy elderly participants (ages, 55-84 years) were included in this study. High-resolution 3D T1-spoiled gradient recalled-echo (SPGR) images were obtained using 3T MRI. BSIM-based processing steps included an inhomogeneity correction, intensity normalization, skull stripping, atlas registration, extraction of intensity profiles, and calculation of cortical thickness. Processing steps were automatic, with the exception of semiautomatic skull stripping. Individual cortical thicknesses were compared to a database indicating mean cortical thickness of healthy adults, in order to produce Z-score thinning maps. Intra-class correlation coefficients (ICCs) were calculated in order to evaluate inter-rater and intra-rater reliabilities. Results: ICCs for intra-rater reliability were excellent, ranging from 0.751-0.940 in brain regions except the right occipital, left anterior cingulate, and left and right cerebellum (ICCs = 0.65-0.741). Although ICCs for inter-rater reliability were fair to excellent in most regions, poor inter-rater correlations were observed for the cingulate and occipital regions. Processing time, including manual skull stripping, was $17.07{\pm}3.43min$. Z-score maps for all participants indicated that cortical thicknesses were not significantly different from those in the comparison databases of healthy adults. Conclusion: BSIM-based cortical thickness measurements provide acceptable intra-rater and inter-rater reliability. We therefore suggest BSIM-based cortical thickness analysis as an adjunct clinical tool to detect cortical atrophy.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.101-105
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• 2016

The number of deaths is often measured to monitor the population health status and priority of health problems. However, number of years of life lost (YLL) is a more appropriate indicator in some cases. We have calculated the YLL of adult cancers and its trend over the past few years in Yazd to provide planners with baseline data. Data obtained from death registration system were used to calculate the YLL, based on each individual's age at death, and the standardized expected YLL method was applied with a discount rate of 0.03, an age weight of 0.04, and a correction factor of 0.165. All data were analyzed and prepared in Epi6 and Excel 2007. A total of 3,850 death records were analyzed. Some 550 patients in Yazd province aged ${\geq}20$ die annually due to cancer (male: female ratio 1.3). The average ages at death in lung, CNS, breast cancer and leukemia cases were 68.5, 59, 58.7 and 61, respectively. The age group of 40-59 with 21 % had the highest cancer mortality percentage. Premature cancer deaths have caused 40,753 YLL (5,823 YLL annually). Females lose on average more life years to cancer than do men (11.6 vs 9.8 years). Lung cancer (12.1%), CNS tumors (11.7%) and leukemia (11.4 %) were the leading causes terms of YLL due to all cancers in both sexes. From 2004 to 2010, cancer-caused YLL as a fraction of all YLL increased from 12.8 to 15.2 %. This study can help in the assessment of health care needs and prioritization. Cancer is the major cause of deaths and the trend is increasing. The use of YLLs is a better index for measurement of premature mortality for ranking of diseases than is death counts. Longer periods of observation will make these trends more robust and will help to evaluate and develop, better public health interventions.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.345-347
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• 2012

본 논문에서는 4-조각 전립선 병리조직 영상을 기하 보정 및 강체 정합하여 자동 스티칭하는 방법을 제안한다. 4-조각 병리영상에 대하여 총 3번의 스티칭을 수행하는데, 좌, 우 조각영상의 상, 하 영상 간 스티칭을 각각 수행 한 후 좌, 우 조각 영상 간 스티칭을 수행한다. 강체 정합 전 병리 조각의 코너를 이용해 x-축, y-축 방향의 위치보정과 회전보정을 수행하는 기하보정 단계를 거침으로서 지역적 최적해로의 수렴을 방지하며, 강체 정합의 정확성을 높인다. 병리영상은 전체적으로 밝기값이 유사하므로 밝기값이 아닌 외곽선 정보를 이용하여 조각 영상간의 거리를 최소화시켜 강체 정합한다. 실험 결과, 4-조각 전립선 병리조직 영상이 지역적 최적해에 수렴하지 않고, 조각 영상 간 거리를 최소화 하며, 하나로 스티칭 됨을 확인할 수 있었다. 제안 방법의 총 수행 시간은 평균 10.32초로 측정되었다. 본 논문의 제안 방법은 4조각으로 나뉜 전립선 병리조직 영상을 하나로 스티칭 함으로서 해당 조직의 전체 구조 파악 및 조직 내에서의 암의 위치 파악에 사용 될 수 있으며 이를 통한 전립선암의 확진에도 사용 될 수 있다.

• Journal of Satellite, Information and Communications
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• v.6 no.2
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• pp.1-9
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• 2011

The Communication Ocean and Meteorological Satellite(COMS), the first geostationary observation satellite, was successfully launched on June 27th in 2010. The raw data of Meteorological Imager(MI) and Geostationary Ocean Color Imager(GOCI), the main payloads of COMS, is delivered to end-users through the on-ground processing. The COMS Image Data Acquisition and Control System(IDACS) developed by Korea Aerospace Research Institute(KARI) in domestic technologies performs radiometric and geometric corrections to raw data and disseminates pre-processed image data and additional data to end-users through the satellite. Currently the IDACS is in the nominal operations phase after successful in-orbit testing and operates in National Meteorological Satellite Center, Korea Ocean Satellite Center, and Satellite Operations Center, During the in-orbit test period, validations on functionalities and performance IDACS were divided into 1) image data acquisition and transmission, 2) preprocessing of MI and GOCI raw data, and 3) end-user dissemination. This paper presents that IDACS' operational validation results performed during the in-orbit test period after COMS' launch.

• Radiation Oncology Journal
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• v.25 no.1
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• pp.54-61
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• 2007

[ $\underline{Purpose}$ ]: The purpose of this study is to develop a practical method for determining accurate marker positions for prostate cancer radiotherapy using CT images and kV x-ray images obtained from the use of the on- board imager (OBI). $\underline{Materials\;and\;Methods}$: Three gold seed markers were implanted into the reference position inside a prostate gland by a urologist. Multiple digital image processing techniques were used to determine seed marker position and the center-of-mass (COM) technique was employed to determine a representative reference seed marker position. A setup discrepancy can be estimated by comparing a computed $COM_{OBI}$ with the reference $COM_{CT}$. A proposed algorithm was applied to a seed phantom and to four prostate cancer patients with seed implants treated in our clinic. $\underline{Results}$: In the phantom study, the calculated $COM_{CT}$ and $COM_{OBI}$ agreed with $COM_{actual}$ within a millimeter. The algorithm also could localize each seed marker correctly and calculated $COM_{CT}$ and $COM_{OBI}$ for all CT and kV x-ray image sets, respectively. Discrepancies of setup errors between 2D-2D matching results using the OBI application and results using the proposed algorithm were less than one millimeter for each axis. The setup error of each patient was in the range of $0.1{\pm}2.7{\sim}1.8{\pm}6.6\;mm$ in the AP direction, $0.8{\pm}1.6{\sim}2.0{\pm}2.7\;mm$ in the SI direction and $-0.9{\pm}1.5{\sim}2.8{\pm}3.0\;mm$ in the lateral direction, even though the setup error was quite patient dependent. $\underline{Conclusion}$: As it took less than 10 seconds to evaluate a setup discrepancy, it can be helpful to reduce the setup correction time while minimizing subjective factors that may be user dependent. However, the on-line correction process should be integrated into the treatment machine control system for a more reliable procedure.