• Journal of the Korean Society of Radiology
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• v.12 no.4
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• pp.497-503
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• 2018

The purpose of this study was to investigate the degree of image degradation and the improvement of image quality caused by the density difference between the orthodontic filling material and the surrounding anatomical structure during the examination of the facial CT by quantitative and qualitative analysis. The teeth were scanned using 64-MDCT (Discovery 750 HD, GE HEALTH CARE, Milwaukee, USA). The teeth were scanned and compared according to tube voltage, silicone application, and MAR application. As a result, 10.36% CT value decreased at 140 kVp and 5.81% decrease at the application of silicon material. As a result of the qualitative evaluation, it was evaluated that 7 of the 10 observers and 3 of the acceptors were applied to the MAR algorithm. Therefore, it is possible to reduce the unnecessary burden on the radiation exposure dose as well as to reduce the loss of image data by reducing the high density artifacts, as well as the inspection parameters used in the current clinical application and various algorithms that can reduce the high density artifacts. It can be expected to provide a lot of image information.

• Journal of radiological science and technology
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• v.38 no.4
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• pp.375-381
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• 2015

Digital Radiography is a big part of diagnostic radiology. Because uncorrected digital radiography image supported false effect of Patient's health care. We must be manage the correct digital radiography image. Thus, the artifact images can have effect to make a wrong diagnosis. We report types of occurrence by analyzing the artifacts that occurs in digital radiography system. We had collected the artifacts occurred in digital radiography system of general hospital from 2007 to 2014. The collected data had analyzed and then had categorize as the occurred causes. The artifacts could be categorized by hardware artifacts, software artifacts, operating errors, system artifacts, and others. Hardware artifact from a Ghost artifact that is caused by lag effect occurred most frequently. The others cases are the artifacts caused by RF noise and foreign body in equipments. Software artifacts are many different types of reasons. The uncorrected processing artifacts and the image processing error artifacts occurred most frequently. Exposure data recognize (EDR) error artifacts, the processing error of commissural line, and etc., the software artifacts were caused by various reasons. Operating artifacts were caused when the user didn't have the full understanding of the digital medical image system. System artifacts had appeared the error due to DICOM header information and the compression algorithm. The obvious artifacts should be re-examined, and it could result in increasing the exposure dose of the patient. The unclear artifact leads to a wrong diagnosis and added examination. The ability to correctly determine artifact are required. We have to reduce the artifact occurrences by understanding its characteristic and providing sustainable education as well as the maintenance of the equipments.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.28-34
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• 2012

Various feature extraction algorithms are widely applied to real-time image processing applications for extracting significant features from images. Feature extraction algorithms are mostly combined with image processing algorithms mostly for image tracking and recognition. Feature extraction function is used to supply feature information to the other image processing algorithms and it is mainly implemented in a preprocessing stage. Nowadays, image processing applications are faced with embedded system implementation for a real-time processing. In order to satisfy this requirement, it is necessary to reduce execution time so as to improve the performance. Reducing the time for executing a feature extraction function dose not only extend the execution time for the other image processing algorithms, but it also helps satisfy a real-time requirement. This paper explains FAST (Feature from Accelerated Segment Test algorithm) of E. Rosten and presents FPGA-based embedded hardware accelerator architecture. The proposed acceleration scheme can be implemented by using approximately 2,217 Flip Flops, 5,034 LUTs, 2,833 Slices, and 18 Block RAMs in the Xilinx Vertex IV FPGA. In the Modelsim - based simulation result, the proposed hardware accelerator takes 3.06 ms to extract 954 features from a image with $640{\times}480$ pixels and this result shows the cost effectiveness of the propose scheme.

• Journal of the Korean Society of Radiology
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• v.4 no.2
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• pp.21-25
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• 2010

Recently, various semiconductor compounds as radiation detection material have been researched for a diagnostic x-ray detector application. In this paper, we have fabricated the CdS detecton sensor that has good photosensitivity and high x-ray absorption efficiency among other semiconductor compounds, and evaluated the application feasibility by investigating the detection properties about energy range of diagnostic x-ray generator. We have fabricated the line voltage selector(LCV) for a signal acquisition and quantities of CdS sensor, and designed the voltage detection circuit and rectifying circuit. Also, we have used a relative relation algorithm according to x-ray exposure condition, and fabricated the interface board with DAC controller. Performance evaluation was investigated by data processing using ANOVA program from voltage profile characteristics according to resistive change obtained by a tube voltage, tube current, and exposure time that is a exposure condition of x-ray generator. From experimental results, an error rates were reduced according to increasing of a tube voltage and tube current, and a good properties of 6%(at 90 kVp) and 0.4%(at 320 mA) ere showed. and coefficient of determination was 0.98 with relative relation of 1:1. The error rate according to x-ray exposure time showed exponential reduction because of delayed response velocity of CdS material, and the error rate has 2.3% at 320 msec. Finally, the error rate according to x-ray dose is below 10%, and a high relative relation was showed with coefficient of determination of 0.9898.

• The Journal of the Society of Stroke on Korean Medicine
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• v.6 no.1
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• pp.25-32
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• 2005

Background and purpose: Arterial stiffness is an important, independent determinant of cardiovascular risk. Pulse wave velocity (PWV) has been used as a valuable index of arterial stiffness and as a surrogate marker for atherosclerosis. The Framingham risk score was developed using categorized risk factors to predict the 10 year absolute risk of developing coronary heart disease (CHD). This algorithm is established using recommended guidelines for blood pressure, total cholesterol, and high density lipoprotein cholesterol in addition to age, smoking history and history of diabetes. Tongxinluo(TXL) has been shown to have anti hyperlipidemic activity and anti atherogenic effects. To determine its efficacy and safety, we examined whether TXL improves PWV, ABI, Framingham score, blood pressure, and lipid profile in high risk group of cardiovascular diseases. Subjects and methods: 49 subjects with the high risk of cardiovascular diseases were recruited. Subjects were administered TXL with the dose of 1110mg three times a day for 8 weeks. baPWV, ABI, Framingham risk score, Blood pressure and serum lipid profile were assessed at baseline and after 4 and 8weeks. Results: Total cholesterol, LDL cholesterol, triglyceride, total lipid and phospolipid significantly decreased after 4 weeks of medication. Total cholesterol, total lipid and phospolipid significantly decreased after 8 weeks of medication. There were no significant changes in Framingham risk scores, ABI, PWV and blood pressure. On safety assessment, there were no adverse effects, hepatic or renal toxicity. Conclusion: We suggest that TXL is a safe and useful herbal medicine for hyperlipidemia and as for anti-atherognic effects, further research would be necessary.

• Progress in Medical Physics
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• v.23 no.2
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• pp.91-98
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• 2012

Verification of internal organ motion during treatment and its feedback is essential to accurate dose delivery to the moving target. We developed an offline based internal organ motion verification system (IMVS) using cine EPID images and evaluated its accuracy and availability through phantom study. For verification of organ motion using live cine EPID images, a pattern matching algorithm using an internal surrogate, which is very distinguishable and represents organ motion in the treatment field, like diaphragm, was employed in the self-developed analysis software. For the system performance test, we developed a linear motion phantom, which consists of a human body shaped phantom with a fake tumor in the lung, linear motion cart, and control software. The phantom was operated with a motion of 2 cm at 4 sec per cycle and cine EPID images were obtained at a rate of 3.3 and 6.6 frames per sec (2 MU/frame) with $1,024{\times}768$ pixel counts in a linear accelerator (10 MVX). Organ motion of the target was tracked using self-developed analysis software. Results were compared with planned data of the motion phantom and data from the video image based tracking system (RPM, Varian, USA) using an external surrogate in order to evaluate its accuracy. For quantitative analysis, we analyzed correlation between two data sets in terms of average cycle (peak to peak), amplitude, and pattern (RMS, root mean square) of motion. Averages for the cycle of motion from IMVS and RPM system were $3.98{\pm}0.11$ (IMVS 3.3 fps), $4.005{\pm}0.001$ (IMVS 6.6 fps), and $3.95{\pm}0.02$ (RPM), respectively, and showed good agreement on real value (4 sec/cycle). Average of the amplitude of motion tracked by our system showed $1.85{\pm}0.02$ cm (3.3 fps) and $1.94{\pm}0.02$ cm (6.6 fps) as showed a slightly different value, 0.15 (7.5% error) and 0.06 (3% error) cm, respectively, compared with the actual value (2 cm), due to time resolution for image acquisition. In analysis of pattern of motion, the value of the RMS from the cine EPID image in 3.3 fps (0.1044) grew slightly compared with data from 6.6 fps (0.0480). The organ motion verification system using sequential cine EPID images with an internal surrogate showed good representation of its motion within 3% error in a preliminary phantom study. The system can be implemented for clinical purposes, which include organ motion verification during treatment, compared with 4D treatment planning data, and its feedback for accurate dose delivery to the moving target.

• The Journal of the Acoustical Society of Korea
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• v.20 no.4
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• pp.35-41
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• 2001

This paper describes Linear Discriminant Analysis and common vector extraction for speech recognition. Voice signal contains psychological and physiological properties of the speaker as well as dialect differences, acoustical environment effects, and phase differences. For these reasons, the same word spelled out by different speakers can be very different heard. This property of speech signal make it very difficult to extract common properties in the same speech class (word or phoneme). Linear algebra method like BT (Karhunen-Loeve Transformation) is generally used for common properties extraction In the speech signals, but common vector extraction which is suggested by M. Bilginer et at. is used in this paper. The method of M. Bilginer et al. extracts the optimized common vector from the speech signals used for training. And it has 100％ recognition accuracy in the trained data which is used for common vector extraction. In spite of these characteristics, the method has some drawback-we cannot use numbers of speech signal for training and the discriminant information among common vectors is not defined. This paper suggests advanced method which can reduce error rate by maximizing the discriminant information among common vectors. And novel method to normalize the size of common vector also added. The result shows improved performance of algorithm and better recognition accuracy of 2％ than conventional method.