• Journal of Biomedical Engineering Research
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• v.31 no.2
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• pp.94-98
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• 2010

In magnetic resonance electrical impedance tomography (MREIT), a current-injection MR imaging method is adopted to produce a cross-sectional image of an electrical conductivity distribution in addition to MR images. The purpose of this study was to test the feasibility of MREIT for differentiating the canine lung parenchyma without and with pneumonia. Three normal healthy beagles and two mixed breed dogs with pneumonia were used. After attaching electrodes around the chest, we placed the dog inside our MR scanner. We injected as much as 30 mA current in a form of short pulses into the chest region. Reconstructed conductivity images of normal canine lungs exhibit a peculiar pattern of a relatively coarse salt and pepper noise. On the contrary, conductivity images of pneumonic canine lungs show significantly enhanced contrast of the lesions while the corresponding MR images show a little bit of contrast in the middle and caudal lung parenchyma due to the accumulation of pleural fluid. This preliminary study indicates that MREIT imaging of the chest may deliver unique new diagnostic information.

• Proceedings of the KOSOMBE Conference
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• v.1992 no.05
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• pp.55-57
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• 1992

Image display is the last step of imaging chain in which the diagnostic information is transformed into perceivable intensities and transformed to observer's eye-brain system. In this process, a certain part of information may be efficiently transfered and another part may be inefficiently transfered leading to information loss. In this study, the visual perceptual properties of image display on CRT monitor has been investigated. Psychophysical experiment of target image detection has been performed using CRT monitor for various background grey levels, and the threshold difference grey levels required for visual discrimination have been predicted by computer simulation with visual model.

• Journal of the Korea Society of Computer and Information
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• v.20 no.9
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• pp.121-128
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• 2015

In this paper, we proposed and implemented the effective automatic foreground motion detection algorithm that detect the foreground motion by analyzing the digital video data that captured by the network camera. We classified the background as moving background, fixed background and normal background based on the standard deviation of background and used it to detect the foreground motion. According to the result of experiment, our algorithm decreased the fault detection of the moving background and increased the accuracy of the foreground motion detection. Also it could extract foreground more exactly by using the statistic information of background in the phase of our foreground extraction.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.463-464
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• 2007

This study describes a method of a human sensibility evaluation using photoplethysmogram(PPG) signal and a biofeedback algorithm to enhance the sensibility For this objective, the heart rate variability(HRV) is extracted from the PPG signal and using the HRV and its FFT the human sensibility is evaluated. The biofeedback algorithm is designed with motion image player interacting with the results of sensibility evaluation. The sensibility evaluation test showed feasibility of the designed method.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1906-1908
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• 2007

This study describes a software engine that can evaluate human sensibility using a heart rate variable(HRV) of hypochodriac or old people, and suggest biofeedback to enhance their emotion. To develop the software engine, using PPG signal heart rate and HRV are calculated. Using the FFT spectra of HRV, human sensibility is estimated. And a biofeedback software is designed with motion image player, breathing control and other function modules.

• Journal of the Korean Society for information Management
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• v.31 no.1
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• pp.231-250
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• 2014

Due to the recent development of Information and Communication Technologies (ICT), the amount of research publications has increased exponentially. In response to this rapid growth, the demand of automated text processing methods has risen to deal with massive amount of text data. Biomedical text mining discovering hidden biological meanings and treatments from biomedical literatures becomes a pivotal methodology and it helps medical disciplines reduce the time and cost. Many researchers have conducted literature-based discovery studies to generate new hypotheses. However, existing approaches either require intensive manual process of during the procedures or a semi-automatic procedure to find and select biomedical entities. In addition, they had limitations of showing one dimension that is, the cause-and-effect relationship between two concepts. Thus;this study proposed a novel approach to discover various relationships among source and target concepts and their intermediate concepts by expanding intermediate concepts to multi-levels. This study provided distinct perspectives for literature-based discovery by not only discovering the meaningful relationship among concepts in biomedical literature through graph-based path interference but also being able to generate feasible new hypotheses.

• Genomics & Informatics
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• v.18 no.2
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• pp.15.1-15.6
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• 2020

Named entity recognition tools are used to identify mentions of biomedical entities in free text and are essential components of high-quality information retrieval and extraction systems. Without good entity recognition, methods will mislabel searched text and will miss important information or identify spurious text that will frustrate users. Most tools do not capture non-contiguous entities which are separate spans of text that together refer to an entity, e.g., the entity "type 1 diabetes" in the phrase "type 1 and type 2 diabetes." This type is commonly found in biomedical texts, especially in lists, where multiple biomedical entities are named in shortened form to avoid repeating words. Most text annotation systems, that enable users to view and edit entity annotations, do not support non-contiguous entities. Therefore, experts cannot even visualize non-contiguous entities, let alone annotate them to build valuable datasets for machine learning methods. To combat this problem and as part of the BLAH6 hackathon, we extended the TextAE platform to allow visualization and annotation of non-contiguous entities. This enables users to add new subspans to existing entities by selecting additional text. We integrate this new functionality with TextAE's existing editing functionality to allow easy changes to entity annotation and editing of relation annotations involving non-contiguous entities, with importing and exporting to the PubAnnotation format. Finally, we roughly quantify the problem across the entire accessible biomedical literature to highlight that there are a substantial number of non-contiguous entities that appear in lists that would be missed by most text mining systems.

• Proceedings of the Korean Vacuum Society Conference
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• 2015.08a
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• pp.51.2-51.2
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• 2015

Understanding interfacial phenomena has been one of the main research issues not only in semiconductors but only in life sciences. I have been trying to meet the atomic scale surface and interface analysis challenges from semiconductor industries and furthermore to extend the application scope to biomedical areas. Optical imaing has been most widely and successfully used for biomedical imaging but complementary ion beam imaging techniques based on mass spectrometry and ion scattering can provide more detailed molecular specific and nanoscale information In this presentation, I will review the 27 years history of medium energy ion scattering (MEIS) development at KRISS and DGIST for nanoanalysis. A electrostatic MEIS system constructed at KRISS after the FOM, Netherland design had been successfully applied for the gate oxide analysis and quantitative surface analysis. Recenlty, we developed time-of-flight (TOF) MEIS system, for the first time in the world. With TOF-MEIS, we reported quantitative compositional profiling with single atomic layer resolution for 0.5~3 nm CdSe/ZnS conjugated QDs and ultra shallow junctions and FINFET's of As implanted Si. With this new TOF-MEIS nano analysis technique, details of nano-structured materials could be measured quantitatively. Progresses in TOF-MEIS analysis in various nano & bio technology will be discussed. For last 10 years, I have been trying to develop multimodal nanobio imaging techniques for cardiovascular and brain tissues. Firstly, in atherosclerotic plaque imaging, using, coherent anti-stokes raman scattering (CARS) and time-of-flight secondary ion mass spectrometry (TOF-SIMS) multimodal analysis showed that increased cholesterol palmitate may contribute to the formation of a necrotic core by increasing cell death. Secondly, surface plasmon resonance imaging ellipsometry (SPRIE) was developed for cell biointerface imaging of cell adhesion, migration, and infiltration dynamics for HUVEC, CASMC, and T cells. Thirdly, we developed an ambient mass spectrometric imaging system for live cells and tissues. Preliminary results on mouse brain hippocampus and hypotahlamus will be presented. In conclusions, multimodal optical and mass spectrometric imaging privides overall structural and morphological information with complementary molecular specific information, which can be a useful methodology for biomedical studies. Future challenges in optical and mass spectrometric imaging for new biomedical applications will be discussed.

• Journal of Biomedical Engineering Research
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• v.32 no.3
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• pp.185-190
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• 2011

The purpose of this study is to investigate the influence of organism vigor information solution(OVIS) on the animal cell growth and to set up a condition for cell culture. We investigated the reactions on the MG-63 and MCF-7 cell line in mixture culture media with various amount of REVIEW solution, which is an example among various OVIS. DMEM-HG was used as basic media. The concentration range of the mixture was limited from 0% to 15%. MTT assay is used for cell viability test. The cell was incubated for 14days and the MTT assay was performed on day 1, 3, 7, 10 and 14 throughout the experiment. We used the ELISA reader to measure the Optical Density(O.D) at 595 nm wavelength filter. MCF-7 was linearly proliferated according to culture time and concentrations of OVIS. On the other hand, MG-63 cells were measured the highest O.D value at 12%. The growth rates of both cells cultured in mixed culture media with OVIS are much higher than those in only basic media, DMEMHG, after 14days. It was confirmed that cell cultured at OVIS grows rapidly at certain period although cells showed a negative effect in initial stage.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2004.11a
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• pp.104-107
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• 2004

In this study, using brain phantom for multi-modality imaging, we acquired CT, MR and PET images and performed registration of these anatomical images and nuclear medicine functional images. The algorithms and program applied for registration were Chamfer Matching and Mutual Information Maximization algorithm which have been using frequently in clinic and verified accuracy respectively. In result, both algorithms were useful methods for CT-MR, CT-PET and MR-PET. But Mutual Information Maximization was more effective algorithm for low resolution image as nuclear medicine functional image.