• Journal of the Institute of Convergence Signal Processing
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• v.24 no.4
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• pp.205-212
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• 2023

Among cardiac diseases, arrhythmias can lead to serious complications such as stroke, heart attack, and heart failure if left untreated, so continuous and accurate ECG monitoring is crucial for clinical care. However, the accurate interpretation of electrocardiogram (ECG) data is entirely dependent on medical doctors, which requires additional time and cost. Therefore, this paper proposes an arrhythmia recognition module for the purpose of developing a medical platform through the analysis of abnormal pulse waveforms based on Lifelogs. The proposed method is to convert ECG data into image format instead of time series data, apply visual pattern recognition technology, and then detect arrhythmia using CNN model. In order to validate the arrhythmia classification of the CNN model by image type conversion of ECG data proposed in this paper, the MIT-BIH arrhythmia dataset was used, and the result showed an accuracy of 97%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.12
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• pp.764-770
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• 2014

It is expected that the techniques of optical imaging through turbid media enables non-invasive imaging through human skin and biological tissues. In recent years, many researches have shown that imaging through turbid media can be made possible by measuring the transmission matrix (TM) of the turbid medium and utilizing it for image recovery. However, this TM based image recovery requires a huge amount of data acquisition and post signal processing of them. Very recently, there were new results that this problem of huge data acquisition and processing can be resolved by using the compressed sensing (CS) framework. CS is a relatively new signal acquisition and reconstruction framework which makes possible to recover the signal of interest correctly with significantly smaller number of signal measurements. In this paper, the TM-based image recovery in imaging through turbid media is reviewed and the recent progress made by using CS is introduced.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2717-2723
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• 2015

Recently, digital image processing is being applied in various areas of broadcasting, communication, computer graphic and medical science. But, degradation of images occurs in the process of digital image acquisition, processing and transmission. Therefore, in order to remove the mixed noise, this paper suggested the image restoration algorithm to process salt and pepper noise with weighted filters according to 4 direction pixel changes after judging the noise and to process AWGN with weighted filters which have individually different characteristics. Regarding the processed results by applying Boat images which were corrupted by salt and pepper noise(P=40%), suggested algorithm showed the improvement by 1.33[dB], 1.41[dB], 0.51[dB] respectively compared with the existing CWMF, AWMF, MMF.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.281-288
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• 2009

This paper proposes a novel algorithm for the efficient classification and annotation of medical images, especially X-ray images. Since X-ray images have a bright foreground against a dark background, we need to extract the different visual descriptors compare with general nature images. In this paper, a Color Structure Descriptor (CSD) based on Harris Corner Detector is only extracted from salient points, and an Edge Histogram Descriptor (EHD) used for a textual feature of image. These two feature vectors are then applied to a multi-class Support Vector Machine (SVM), respectively, to classify images into one of 20 categories. Finally, an image has the Annotation Code Array based on the pre-defined hierarchical relations of categories and priority code order, which is given the several optimal keywords by the Annotation Code Array. Our experiments show that our annotation results have better annotation performance when compared to other method.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.07a
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• pp.388-389
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• 2005

In this paper, the electric properties of mercury Iodide multi-layer samples has been investigated. We measured and analyzed their performance parameters such as the X-ray sensitivity and dark-current for a mercury Iodide multi-layer X-ray detector with a dielectric layer. The digital X-ray image detector can be constructed by integrating photoconduction multi-layer that dielectric layer has characteristics of low dark-current, high X-ray sensitivity. However this process has found to have complexity on the performance of the sample. We have investigate dielectric layer that it substitute dielectric layer for HgO(Mercury Oxide). We have employed two approaches for producing the mercury Iodide sample : 1) Physical Vapor Deposition(PVD) and 2) Particle-In-Binder(PIB). In this paper fabricated by PIB Method with thicknesses ranging from approximately 180um to 240um and we could produce high-quality samples for each technique particular application. As results, the dielectric materials such as HgO between the dielectric layer and the top electrode may reduce the dark-current of the samples. Mercury Iodide multi-layer having HgO has characteristics of low dark-current, high X-ray sensitivity and simple processing. So we can acquired a enhanced signal to noise ratio. In this paper offer the method can reduce the dark-current in the X-ray detector.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.3
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• pp.102-109
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• 2009

Purpose: Flash 3D (pixon(R) method; 3D OSEM) was developed as a software program to shorten exam time and improve image quality through reconstruction, it is an image processing method that usefully be applied to nuclear medicine tomography. If perfoming brain diamox perfusion scan by reconstructing subtracted images by Flash 3D with shortened image acquisition time, there was a problem that SNR of subtracted image is lower than basal image. To increase SNR of subtracted image, we use LEAP collimators, and we emphasized on sensitivity of vessel dilatation than resolution of brain vessel. In this study, our purpose is to confirm possibility of application of LEAP collimators at brain diamox perfusion tomography, identify proper reconstruction factors by using Flash 3D. Materials and methods: (1) The evaluation of phantom: We used Hoffman 3D Brain Phantom with $^{99m}Tc$. We obtained images by LEAP and LEHR collimators (diamox image) and after 6 hours (the half life of $^{99m}Tc$: 6 hours), we use obtained second image (basal image) by same method. Also, we acquired SNR and ratio of white matters/gray matters of each basal image and subtracted image. (2) The evaluation of patient's image: We quantitatively analyzed patients who were examined by LEAP collimators then was classified as a normal group and who were examined by LEHR collimators then was classified as a normal group from 2008. 05 to 2009. 01. We evaluate the results from phantom by substituting factors. We used one-day protocol and injected $^{99m}Tc$-ECD 925 MBq at both basal image acquisition and diamox image acquisition. Results: (1) The evaluation of phantom: After measuring counts from each detector, at basal image 41~46 kcount, stress image 79~90 kcount, subtraction image 40~47 kcount were detected. LEAP was about 102~113 kcount at basal image, 188~210 kcount at stress image and 94~103 at subtraction image kcount were detected. The SNR of LEHR subtraction image was decreased than LEHR basal image about 37%, the SNR of LEAP subtraction image was decreased than LEAP basal image about 17%. The ratio of gray matter versus white matter is 2.2:1 at LEHR basal image and 1.9:1 at subtraction, and at LEAP basal image was 2.4:1 and subtraction image was 2:1. (2) The evaluation of patient's image: the counts acquired by LEHR collimators are about 40~60 kcounts at basal image, and 80~100 kcount at stress image. It was proper to set FWHM as 7 mm at basal and stress image and 11mm at subtraction image. LEAP was about 80~100 kcount at basal image and 180~200 kcount at stress image. LEAP images could reduce blurring by setting FWHM as 5 mm at basal and stress images and 7 mm at subtraction image. At basal and stress image, LEHR image was superior than LEAP image. But in case of subtraction image like a phantom experiment, it showed rough image because SNR of LEHR image was decreased. On the other hand, in case of subtraction LEAP image was better than LEHR image in SNR and sensitivity. In all LEHR and LEAP collimator images, proper subset and iteration frequency was 8 times. Conclusions: We could archive more clear and high SNR subtraction image by using proper filter with LEAP collimator. In case of applying one day protocol and reconstructing by Flash 3D, we could consider application of LEAP collimator to acquire better subtraction image.

• Korean Journal of Metals and Materials
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• v.50 no.5
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• pp.401-406
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• 2012

When viewed using a magnetic resonance imaging (MRI) system, invasive materials inside the human body, in many cases, severely distort the MR image of human tissues. The degree of the MR image distortion increases in proportion not only to the difference in the susceptibility between the invasive material and the human tissue, but also to the intensity of the magnetic field induced by the MRI system. In this study, by blending paramagnetic Ti particles with diamagnetic graphite, we synthesized $Ti_{100-x}C_x$ composites that can reduce the artifact in the MR image under the high-strength magnetic field. Of the developed composites, $Ti_{70}C_{30}$ showed the magnetic susceptibility of ${\chi}=67.6{\times}10^{-6}$, which corresponds to 30% of those of commercially available Ti alloys, the lowest reported in the literature. The level of the MR image distortion in the vicinity of the $Ti_{70}C_{30}$ composite insert was nearly negligible even under the high magnetic field of 4.7 T. In this paper, we reported on a methodology of designing new structural materials for bio-applications, their synthesis, experimental confirmation and measurement of MR images.

• The KIPS Transactions:PartB
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• v.17B no.6
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• pp.437-444
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• 2010

In this paper, we propose a method of analysing the relation between the patient's face color and his(her) kidney disease using image processing technology. This method is based on the ocular inspection which is one of the most famous diagnosis methods used in the oriental medical system. The way of processing and analysing the face image, which is for visualization and objectification of the color difference, is included. The objects are selected from the patients who suffer the kidney disease and use the hemodialyzer. Their facial images and clinical data are collected. From these data, we propose a hypothesis that the color of the patient's face is changed according to the patient's kidney state. At the same time, we present two algorithms of extracting the specific part of face which can identify the state of the patient's kidney and tracing the history of the color's change. This proposed method is evaluated through the practical experiments and their analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.964-971
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• 2003

According to the development of information processing technology and computer hardware, PACS systems have been installed in many hospitals. They can increase the efficiency and the convenience remarkably for handling medical images using digitalized data. After we compare the generation images with other cases, we can read the images correctly and decide how to treat the patients. If the results, included test method and specialist's opinion, are represented dynamically on homepage in hospital. then visitors can get their experience in directly and understand the field of examination and the area of medical treatment. In this thesis, we display the effective images such as MR of the abnormal cases according to parts and diseases, the movie and still images such as Angio image, the other multimedia materials such as the sound and text of doctor's opinions, in SMIL based on XML, concerning the problem of concurrency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.477-479
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• 2017

With the recent advances in medical technology and health care, the prevention and treatment of diseases has developed. Accordingly aging has rapidly progressed. In this life span and aging society, demand for diagnostic centered medical care is increasing rapidly. In this paper, we propose a wearable patient check system based on FPGA that can be controlled by sensors. In the existing hospital, a doctor or nurse visited the patient every hour to check the condition. However, in this paper, patients, doctors and nurses can check the patient's condition at the desired time using patient check system. In addition, the tilt sensor is used for the patient who is uncomfortable to easily control. The proposed FPGA-based hardware architecture consists of an algorithm for enlarged image processing, a TFT-LCD Controller, a CIS Controller, and a Memory Controller to output the patient's status image. Implemented and validated using the DE2-115 test board with Cyclone IV EP4CE115F29C7 FPGA device and its operating frequency is 50MHz.