• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.371-378
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• 2000

In this study, we proposed pathological pattern detection system for X-ray chest image using artificial neural network. In a physical examination, radiologists have checked on the chest image projected the view box by a magnifying glass and found out what the disease is. Here, the detection of X-ray fluoroscopy is tedious and time-consuming for human doing. Lowering of efficiency for chest diagnosis is caused by lots mistakes of radiologist because of detecting the micro pathology from the film of small size. So, we proposed the method for disease detection using artificial neural network and digital image processing on a X-ray chest image. This method composes the function of image sampling, median filter, image equalizer used neural network and pattern recognition used neural network. We confirm this method has improved the problem of a conventional method.

• Journal of Radiation Protection and Research
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• v.34 no.1
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• pp.25-30
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• 2009

Micro-columnar CsI(Tl) is the most popular scintillator material which is used for many indirect digital X-ray imaging detectors. The light scattering at the surface of micro-columnar CsI(Tl) scintillator was studied to find the correlation between the surface roughness and the resultant image resolution of indirect X-ray imaging detectors. Using a commercially available optical simulation program, Light Tools, MTF (Modulation Transfer Function) curves of the CsI(Tl) film thermally evaporated on glass substrate with different thickness were calculated and compared with the experimental estimation of MTF values by the edge X-ray image method and CCD camera. It was found that the standard deviation value of Gaussian scattering model which is determined by the surface roughness of micro-columns could certainly change the MTF value of image sensors. This model and calculation methodology will be beneficial to estimate the overall performance of indirect X-ray imaging system with CsI(Tl) scintillator film for optimum design depending on its application.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.1044-1050
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• 2011

The quality of brazing joints is one of the most important factors that have an effect on the performance of the brazing joint-based heat exchangers with the growing use in industry recently. Therefore, it is necessary to inspect the brazing joints in order to guarantee the performance of the heat exchangers. This paper presents a non-destructive method to inspect the brazing joints of the heat exchangers using X-ray. Firstly, X-ray cross-sectional images of the brazing joints are obtained by using CT (Computerized Tomography) technology. Cross-sectional image from CT is more useful to detect the inner defects than the traditional transmitted X-ray image. Secondly, the acquired images are processed by an algorithm proposed for the defect detection of brazing joint. Finally, two types of brazing joint are examined in a series of experiments to detect the defects in brazing joints. The experimental results show that the proposed algorithm is effective for defect detection of the brazing joints in heat exchangers.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.10
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• pp.886-890
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• 2013

In this paper, a 3D coordinates acquisition method for a mechanical assembly is developed by using multiview X-ray images. The multi-view X-ray images of an object are obtained by a rotary table. From the rotation transformation, it is possible to obtain the 3D coordinates of corresponding edge points on multi-view X-ray images by triangulation. The edge detection algorithm in this paper is based on the attenuation characteristic of the X-ray. The 3D coordinates of the object points are represented on a graphic display, which is used for the inspection of a mechanical assembly.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.527-528
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• 2012

• Publications of The Korean Astronomical Society
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• v.15 no.spc1
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• pp.73-83
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• 2000

X-ray astronomy deals with measurements of the electromagnetic radiation in the energy range of $E\~0.1-100 keV (\lambda\~0.12-120{\AA})$. The wavelength of X-ray is comparable to the size of atoms, so that the photons in the X-ray range are usually produced and absorbed by the atomic processes. Since the launch of the first X-ray astronomy satellite 'Uhuru' in 1970, technological advances in a launch capability and a detection capability make X-ray astronomy one of the most rapidly evolving fields of astronomical research. Particularly, a spectral resolving power $E/{\Delta}E$ has been increased by an order of 2 - 3 (in the energy range of 0.1 - 10 keV) during the past 30years. In this paper, I briefly review a developing process of the resolving power and spectroscopic techniques. Then I describe important emission/absorption lines in X-ray astronomy, as well as diagnostics of gas property with line parameters.

• Journal of the Korean institute of surface engineering
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• v.32 no.3
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• pp.239-243
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• 1999

At Present, 200mm wafer technology is being applied for commercial fabrications of 64, 128, and 256 M DRAM devices, and 300mm technology will be evolved for 1G DRAM devices in the early 21th century, recognizing limitations of several process technologies. In particular recognition has been realized in harmful effects of surface contamination of trace metals introduced during devicing processes. Such a guide line for surface metal contamination has been proposed as 1E9 and 1E10 atoms/$\textrm{cm}^2$ of individual metal contamination for wafering and devicing of 1G DRAM, respectively, and so its measurement limit should be at least 1E8 atoms/$\textrm{cm}^2$. The detection limit of present measurement systems is 2E9 atoms/$\textrm{cm}^2$ obtainable with TRXFA(Total Reflection X-Ray Fluorescence Analysis). TRXFA is nondestructive and the simplest in terms of operation, and it maps the whole wafer surfaces but needs detection improvement. X-Ray intensity produced with synchrotron accelerator is much higher than that of conventional X-ray sources by order of 4-5 magnitudes. Hence theoretically its reactivity with silicon surfaces is expected to be much higher than the conventional one, realizing improvement of detection limit. X-ray produced with synchrotron accelerator is illuminated at a very low angle with silicon wafer surfaces such as 0.1 degree and reflects totally. Hence informations only from surface can be collected and utilized without overlapping with bulk informations. This study shows the total reflection phenomenon and quantitative improvement of detection limit for metallic contamination. It is confirmed that synchrotron X-ray can be a very promising alternative for realizing improvement of detection limit for the next generation devices.

• Journal of Astronomy and Space Sciences
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• v.15 no.2
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• pp.341-358
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• 1998

The X-ray astronomy team of the Korea Astronomy Observatory(KAO) is planning to develop a multi-cell proportional counter, adopting an anti-coincidence method to reduce its internal background. We have developed a Monte Carlo code to determine the X-ray detection efficiency of the counter. As a check of our code, we successfully reproduced the detection efficiency of Ginga/LAC. In this paper, we report the simulation results for the counter being considered in KAO.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.35-45
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• 2022

Even in recent years, treatment of first-aid patients is still often delayed due to a shortage of medical resources in marginalized areas. Research on automating the analysis of medical data to solve the problems of inaccessibility for medical services and shortage of medical personnel is ongoing. Computer vision-based medical inspection automation requires a lot of cost in data collection and labeling for training purposes. These problems stand out in the works of classifying lesion that are rare, or pathological features and pathogenesis that are difficult to clearly define visually. Anomaly detection is attracting as a method that can significantly reduce the cost of data collection by adopting an unsupervised learning strategy. In this paper, we propose methods for detecting abnormal images on chest X-RAY images as follows based on existing anomaly detection techniques. (1) Normalize the brightness range of medical images resampled as optimal resolution. (2) Some feature vectors with high representative power are selected in set of patch features extracted as intermediate-level from lesion-free images. (3) Measure the difference from the feature vectors of lesion-free data selected based on the nearest neighbor search algorithm. The proposed system can simultaneously perform anomaly classification and localization for each image. In this paper, the anomaly detection performance of the proposed system for chest X-RAY images of PA projection is measured and presented by detailed conditions. We demonstrate effect of anomaly detection for medical images by showing 0.705 classification AUROC for random subset extracted from the PadChest dataset. The proposed system can be usefully used to improve the clinical diagnosis workflow of medical institutions, and can effectively support early diagnosis in medically poor area.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.869-870
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• 2012