• Progress in Medical Physics
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• v.18 no.2
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• pp.98-106
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• 2007

In June 2005, Yonsei University Medical Center, Severance Hospital upgraded a full-PACS system by adding twenty (5 mega pixels) Totoku ME511L flat panel LCD display devices for diagnostic interpretation purposes. Here we report upon the quantitative (or visual) acceptance testing of the twenty Totoku ME511L display devices for reflection, luminance response, luminance spatial dependency, resolution, noise, veiling glare, and display chromaticity based on AAPM TG 18 report. The tools used in the tests included a telescopic photometer, which was used as a colorimeter, illuminance meter, light sources for reflection assessment, light-blocking devices, and digital TG18 test patterns. For selected 8 flat panel displays, mean diffuse reflection coefficient ($R_d$) was $0.019{\pm}0.02sr^{-1}$. In the luminance response test, luminance ratio (LR), maximum luminance difference ($L_{max}$), and deviation of contrast response were $550{\pm}100,\;2.0{\pm}1.9%\;and\;5.8{\pm}1.8%$, respectively. In the luminance uniformity test, maximum luminance deviation was $14.3{\pm}5.5%$ for the 10% luminance of the TG18-UNL10 test pattern. In the resolution test with luminance measurement method, percent luminance (${\Dalta}L$) at the center was $0.94{\pm}0.64%$. In all cases of noise testing, rectangular target In every square in the three quadrants was visible and all 15 targets except the smallest one in the every corner pattern and the center pattern. The glare ratio (GR) was $12,346{\pm}1,995$. The color uniformity, (u',v'), was $0.0025{\pm}0.0008$. Also, the research results of qualify control guideline of primary disply devices suitable for domestic circumstance are presented All test results are in-line with the criteria recommended by AAPM TG18 report and are thus fully acceptable for diagnostic image interpretation. As a result, the acceptance testing schedule described provides not only an acceptance standard but also guidelines for quality control, optimized viewing conditions, and a means for determining the upgrading time of LCD display devices for diagnostic interpretation.

• The Korean Journal of Nuclear Medicine
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• v.33 no.1
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• pp.65-75
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• 1999

Purpose: The aim of this study is to demonstrate the feasibility of 2-[fluorine-18] fluoro-2-deoxy-D-glucose (F-18-FDG) whole body scan (FDG W/B Scan) using dual-head gamma camera equipped with ultra high energy collimator in patients with various cancers, and compare the results with those of coincidence imaging. Materials and Methods: Phantom studies of planar imaging with ultra high energy and coincidence tomography (FDG CoDe PET) were performed. Fourteen patients with known or suspected malignancy were examined. F-18-FDG whole body scan was performed using dual-head gamma camera with high energy (511 keV) collimators and regional FDG CoDe PET immediately followed it Radiological, clinical follow up and histologic results were correlated with F-18-FDG findings. Results: Planar phantom study showed 13.1 mm spatial resolution at 10 cm with a sensitivity of 2638 cpm/MBq/ml. In coincidence PET, spatial resolution was 7.49 mm and sensitivity was 5351 cpm/MBq/ml. Eight out of 14 patients showed hypermetabolic sites in primary or metastatic tumors in FDG CoDe PET. The lesions showing no hypermetabolic uptake of FDG in both methods were all less than 1 cm except one lesion of 2 cm sized metastatic lymph node. The metastatic lymph nodes of positive FDG uptake were more than 1.5 cm in size or conglomerated lesions of lymph nodes less than 1cm in size. FDG W/B scan showed similar results but had additional false positive and false negative cases. FDG W/B scan could not visualize liver metastasis in one case that showed multiple metastatic sites in FDG CoDe PET. Conclusion: FDG W/B scan with specially designed collimators depicted some cancers and their metastatic sites, although it had a limitation in image quality compared to that of FDG CoDe PET. This study suggests that F-18-FDG positron imaging using dual-head gamma camera is feasible in oncology and helpful if it should be more available by regional distribution of FDG.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.363-373
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• 2020

During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.

• Journal of the Korean earth science society
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• v.30 no.2
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• pp.196-209
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• 2009

Occurrences of sandstorms in the deserts and loess of Mongolia and northern China and associated dustfall episodes in the Korean Peninsula were monitored during the period January through December, 2005. False colour images were made by directly receiving the NOAA Advanced Very High Resolution Radiometer (AVHRR) data, and the distribution and transport of sandstorms were analyzed. The ground concentrations for PM10, PM2.5 and visibility of the dustfall episodes (PM10 concentration over $190{\mu}g\;m^{-3}$) were analyzed at Cheongwon, located midway in South Korea, and in the leeward direction of the place of origin of the sandstorms. Variations in the concentrations of $O_3,\;NO_2$, CO and $SO_2$ were also compared with dust concentrations in the dustfall episodes. Fewer occurrences of strong sandstorms in the place of origin were observed in 2005, due largely to the accumulation of snow and mild fluctuations of high and low pressure systems in the place of origin, thereby accounting for a low frequency of dustfall episodes in Korea, compared with those during the period 1997-2005. A total of 7 dustfall episodes were monitored in Korea in 2005 that lasted 11 days. In summer, sandstorms occurred less frequently in the source region in 2005 due to high humidity and milder winds, thereby causing no dustfall episodes in Korea. In case the sandstorms occurring at the place of source head directly to Korea without passing through large cities and industrial areas of China, the PM2.5 concentrations were measured at 20% or lower than the PM10 concentrations. However, when the sandstorms headed to Korea via the industrial areas of eastern China, where they pick up anthropogenic air pollutants, the PM2.5 concentrations were at least 25% higher of the PM10 concentrations. On the other hand, over 5 cases were observed and analyzed in 2005 where the PM10 concentrations of sand dust originating from the deserts were measured at $190{\mu}g\;m^{-3}$ or lower, falling short of the level of a dustfall episode.

• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.50-58
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• 2005

Recently, the imaging of geological structures beneath water-covered areas has been in great demand because of numerous tunnel and bridge construction projects on river or lake sites. An electrical resistivity survey can be effective in such a situation because it provides a subsurface image of faults or weak zones beneath the water layer. Even though conventional resistivity surveys in water-covered areas, in which electrodes are installed on the water bottom, do give high-resolution subsurface images, much time and effort is required to install electrodes. Therefore, an easier and more convenient method is sought to find the strike direction of the main zones of weakness, especially for reconnaissance surveys. In this paper, we investigate the applicability of the streamer resistivity survey method, which uses electrodes in a streamer cable towed by ship or boat, for delineating a fault zone. We do this through numerical experiments with models of water-covered areas. We demonstrate that the fault zone can be imaged, not only by installing electrodes on the water bottom, but also by using floating electrodes, when the depth of water is less than twice the electrode spacing. In addition, we compare the signal-to-noise ratio and resolving power of four kinds of electrode arrays that can be adapted to the streamer resistivity method. Following this numerical study, we carried out both conventional and streamer resistivity surveys for the planned tunnel construction site located at the Han River in Seoul, Korea. To obtain high-resolution resistivity images we used the conventional method, and installed electrodes on the water bottom along the planned route of the tunnel beneath the river. Applying a two-dimensional inversion scheme to the measured data, we found three distinctive low-resistivity anomalies, which we interpreted as associated with fault zones. To determine the strike direction of these three fault zones, we used the quick and convenient streamer resistivity.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.959-974
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• 2021

Forel-Ule Index (FUI) is an index which classifies the colors of inland and seawater exist in nature into 21 gradesranging from indigo blue to cola brown. FUI has been analyzed in connection with the eutrophication, water quality, and light characteristics of water systems in many studies, and the possibility as a new water quality index which simultaneously contains optical information of water quality parameters has been suggested. In thisstudy, Ocean Colour-Climate Change Initiative (OC-CCI) based 4 km FUI was spatially downscaled to the resolution of 500 m using the Geostationary Ocean Color Imager (GOCI) data and Random Forest (RF) machine learning. Then, the RF-derived FUI was examined in terms of its correlation with various water quality parameters measured in coastal areas and its spatial distribution and seasonal characteristics. The results showed that the RF-derived FUI resulted in higher accuracy (Coefficient of Determination (R²)=0.81, Root Mean Square Error (RMSE)=0.7784) than GOCI-derived FUI estimated by Pitarch's OC-CCI FUI algorithm (R²=0.72, RMSE=0.9708). RF-derived FUI showed a high correlation with five water quality parameters including Total Nitrogen, Total Phosphorus, Chlorophyll-a, Total Suspended Solids, Transparency with the correlation coefficients of 0.87, 0.88, 0.97, 0.65, and -0.98, respectively. The temporal pattern of the RF-derived FUI well reflected the physical relationship with various water quality parameters with a strong seasonality. The research findingssuggested the potential of the high resolution FUI in coastal water quality management in the Korean Peninsula.

• Journal of the Korean Society of Radiology
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• v.15 no.1
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• pp.45-54
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• 2021

This study was written to create educational content in non-destructive fields based on Mixed Reality. Currently, in the field of radiation, there is almost no content for educational Mixed Reality-based educational content. And in the field of non-destructive inspection, the working environment is poor, the number of employees is often 10 or less for each manufacturer, and the educational infrastructure is not built. There is no practical training, only practical training and safety education to convey information. To solve this, it was decided to develop non-destructive worker education content based on Mixed Reality. This content was developed based on Microsoft's HoloLens 2 HMD device. It is manufactured based on the resolution of 1280 ⁎ 720, and the resolution is different for each device, and the Side is created by aligning the Left, Right, Bottom, and TOP positions of Anchor, and the large image affects the size of Atlas. The large volume like the wallpaper and the upper part was made by replacing it with UITexture. For UI Widget Wizard, I made Label, Buttom, ScrollView, and Sprite. In this study, it is possible to provide workers with realistic educational content, enable self-directed education, and educate with 3D stereoscopic images based on reality to provide interesting and immersive education. Through the images provided in Mixed Reality, the learner can directly operate things through the interaction between the real world and the Virtual Reality, and the learner's learning efficiency can be improved. In addition, mixed reality education can play a major role in non-face-to-face learning content in the corona era, where time and place are not disturbed.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.637-654
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• 2023

In recent years, the number of users has been increasing with the rapid development of earth observation satellites. In response, the Committee on Earth Observation Satellites (CEOS) has been striving to provide user-friendly satellite images by introducing the concept of Analysis Ready Data (ARD) and defining its requirements as CEOS ARD for Land (CARD4L). In ARD, a mask called an Unusable Data Mask (UDM), identifying unnecessary pixels for land analysis, should be provided with a satellite image. UDMs include clouds, cloud shadows, terrain shadows, etc. Terrain shadows are generated in mountainous terrain with large terrain relief, and these areas cause errors in analysis due to their low radiation intensity. previous research on terrain shadow detection focused on detecting terrain shadow pixels to correct terrain shadows. However, this should be replaced by the terrain correction method. Therefore, there is a need to expand the purpose of terrain shadow detection. In this study, to utilize CAS500-4 for forest and agriculture analysis, we extended the scope of the terrain shadow detection to shaded areas. This paper aims to analyze the potential for terrain shadow detection to make a terrain shadow mask for South and North Korea. To detect terrain shadows, we used a Hill-shade algorithm that utilizes the position of the sun and a surface's derivatives, such as slope and aspect. Using RapidEye images with a spatial resolution of 5 meters and Sentinel-2 images with a spatial resolution of 10 meters over the Korean Peninsula, the optimal threshold for shadow determination was confirmed by comparing them with the ground truth. The optimal threshold was used to perform terrain shadow detection, and the results were analyzed. As a qualitative result, it was confirmed that the shape was similar to the ground truth as a whole. In addition, it was confirmed that most of the F1 scores were between 0.8 and 0.94 for all images tested. Based on the results of this study, it was confirmed that automatic terrain shadow detection was well performed throughout the Korean Peninsula.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Geophysics and Geophysical Exploration
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• v.8 no.4
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• pp.280-286
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• 2005

Geological sequestration of carbon dioxide ($CO_2$) is one of the most effective strategies far long-term removal of greenhouse gas from atmosphere. This paper reviews three projects for the $CO_2$ sequestration in geological formation. A unique $CO_2$ injection into a marine aquifer has been successfully monitored with repeated surface seismic measurements in the North Sea Sleipner West field. The seismic images reveal the extent and internal shape of the $CO_2$ bubble. Massive miscible $CO_2$ has been injected into a complex fractured carbonate reservoir at the Weyburn oil filed. High-resolution time-lapse P-wave data were successfully obtained to map the features of $CO_2$ movements within the two thin zones of different lithology. From the time-lapse crosswell EM imaging at the Lost Hills oil field in central California, U.S.A., the replacement of brine with $CO_2$ has been confirmed through a decrease of conductivity. The conductivity image was successfully compared with induction logs observed in the two wells.