• Journal of Digital Convergence
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• v.12 no.6
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• pp.433-438
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• 2014

This study aims to get more accurate and objective result by quantifying the result for the sperm changes through the quantitative analysis by the image processing based on the image obtained microscopically for the testicle cell and sperm change appeared with the passage of time when the radiation is irradiated to the white rat testicle. This study has targeted the white rat of 8 weeks lifespan, the X-ray of 6 MV with 1 time of 2 Gy has been irradiated to the whole body. The testicles of 5 rats at each test group immediately after irradiation, after 2 hours of irradiation, 4 hours, 8 hours and 24 hours has been respectively extracted targeting all 30 white rats of normal control group not irradiated by the radiation and the test group. The state of testicle cell and sperm has been observed in the normal control group and the test group by implementing Periodic acid Schiff dyeing after extraction. 24 hours after irradiation, a gradual decrease in sperm count and testicular cells qualitatively and quantitatively that were identified as significant.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.1
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• pp.69-75
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• 2016

Polydimethylsiloxane (PDMS) is used as a scaffold for cell culture. Because both the stress and strain acting on the substrate and the hemodynamic environment are important for studying mechano-transduction of cellular function, the traction force of the surface of a substrate has been measured using fluorescence images of particle distribution. In this study, deformation of the cross-sectional plane of a PDMS block was measured by correlating particle image distributions to validate the particle image strain measurement technique. Deformation was induced by a cone indentor and a shearing parallel plate. Measured deformations from particle image distributions were in agreement with the results of a computational structure analysis using the finite-element method. This study demonstrates that the particle image correlation method facilitates measurement of deformation of a polymer scaffold in the cross-sectional plane.

• Journal of Biomedical Engineering Research
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• v.15 no.4
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• pp.419-427
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• 1994

A new method of digital image analysis technique for discrimination of cancer cell was presented in this paper. The object image was the Thyroid Gland cells image that was diagnosed as normal and abnormal (two types of abnormal : follicular neoplastic cell, and papillary neoplastic cell), respectively. By using the proposed region segmentation algorithm, the cells were segmented into nucleus. The 16 feature parameters were used to calculate the features of each nucleus. As a consequence of using dominant feature parameters method proposed in this paper, discrimination rate of 91.11 % was obtained for Thyroid Gland cells.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.507-518
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• 2021

Magnetic resonance imaging (MRI) is a key technology that has been seeing increasing use in studying the structural and functional innerworkings of the brain. Analyzing the variability of brain connectome through tractography analysis has been used to increase our understanding of disease pathology in humans. However, there lacks standardization of analysis methods for small animals such as mice, and lacks scientific consensus in regard to accurate preprocessing strategies and atlas-based neuroinformatics for images. In addition, it is difficult to acquire high resolution images for mice due to how significantly smaller a mouse brain is compared to that of humans. In this study, we present an Allen Mouse Brain Atlas-based image data analysis pipeline for structural connectivity analysis involving structural region segmentation using mouse brain structural images and diffusion tensor images. Each analysis method enabled the analysis of mouse brain image data using reliable software that has already been verified with human and mouse image data. In addition, the pipeline presented in this study is optimized for users to efficiently process data by organizing functions necessary for mouse tractography among complex analysis processes and various functions.

• Journal of Microbiology
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• v.34 no.4
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• pp.300-304
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• 1996

To define the effects of zooplankton and phytoplankton to bacteria, bacterial numbers, frequency of dividing cells (FDC) and size distribution were performed with image analysis in the surface layer of Lake Soyang. In August 1992, when Anabaena was blooming, the bacterial number increased at daytime. Bacterial numbers and FDC value had a negative correlation (r = 0.83, P < 0.01). Bacterial size spectrums were dynamically changed during the day and night, especially the small bacteria less than $0.5\;{\mu}m^3$. Meanwhile, in October, after the bloom, the bacterial number was only one third of that in August, even though the FDC was higher than that in August. The bacterial numbers of small size class dropped at 13:00. But the size spectrums were relatively constant during the night time. These results suggest that the bacterial growth was tightly coupled with phytoplankton during Anabaena bloom. And after the bloom, the bacterial number was controlled grazing activity of zooplankton at daytime.

• Bulletin of the Korean Chemical Society
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• v.34 no.3
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• pp.815-819
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• 2013

Micropatterns of streptavidin and human epidermal carcinoma A431 cells were successfully imaged, as received and without any labeling, using cluster $Au_3{^+}$ ion beam-based time-of-flight secondary ion mass spectrometry (TOF-SIMS) together with a principal component analysis (PCA). Three different analysis ion beams ($Ga^+$, $Au^+$ and $Au_3{^+}$) were compared to obtain label-free TOF-SIMS chemical images of micropatterns of streptavidin, which were subsequently used for generating cell patterns. The image of the total positive ions obtained by the $Au_3{^+}$ primary ion beam corresponded to the actual image of micropatterns of streptavidin, whereas the total positive-ion images by $Ga^+$ or $Au^+$ primary ion beams did not. A PCA of the TOF-SIMS spectra was initially performed to identify characteristic secondary ions of streptavidin. Chemical images of each characteristic ion were reconstructed from the raw data and used in the second PCA run, which resulted in a contrasted - and corrected - image of the micropatterns of streptavidin by the $Ga^+$ and $Au^+$ ion beams. The findings herein suggest that using cluster-ion analysis beams and multivariate data analysis for TOF-SIMS chemical imaging would be an effectual method for producing label-free chemical images of micropatterns of biomolecules, including proteins and cells.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.2
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• pp.69-79
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• 1994

The conventional machine vision system which has uniform rectangular grid requires tremendous amount of computation for processing and analysing an image especially in 2-D image transfermations such as scaling, rotation and 3-D reconvery problem typical in robot application environment. In this study, the imaging system with nonuiformly distributed image sensors simulating human visual system, referred to as Ploar Exponential Grid(PEG), is compared with the existing conventional uniform rectangular grid system in terms of image resolution and computational complexity. By mimicking the geometric structure of the PEG sensor cell, we obtained PEG-like images using computer simulation. With the images obtained from the simulation, image resolution of the two systems are compared and some basic image processing tasks such as image scaling and rotation are implemented based on the PEG sensor system to examine its performance. Furthermore Fourier transform of PEG image is described and implemented in image analysis point of view. Also, the range and heading-angle measurement errors usually encountered in 3-D coordinates recovery with stereo camera system are claculated based on the PEG sensor system and compared with those obtained from the uniform rectangular grid system. In fact, the PEC imaging system not only reduces the computational requirements but also has scale and rotational invariance property in Fourier spectrum. Hence the PEG system has more suitable image coordinate system for image scaling, rotation, and image recognition problem. The range and heading-angle measurement errors with PEG system are less than those of uniform rectangular rectangular grid system in practical measurement range.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.12
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• pp.90-97
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• 1999

Recently, there have been many researches to automate processing and analysing image data in medical field, due to the advance of image processing techniques, the fast communication network and high performance hardware. In this paper, we design and implement the system based on the multi-layer neural network model to be able to analyze, differentiate and count blood cells in the peripheral blood image. To do these, we segment red and white-blood cell in blood image acquired from microscope with CCD(Charge-coupled device) camera and then apply the various feature extraction algorithms to classify. In addition to, we reduce multi-variate feature number using PCA(Principle Component Analysis) to construct more efficient classifier. So, in this paper, we are sure that the proposed system can be applied to a pathological guided system.

• Proceedings of the Korean Vacuum Society Conference
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• 1997.07a
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• pp.173-176
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• 1997

A numerical analysis of the micro-discharge in an AC pplasma dispplay cell has been made using time-deppendent, 2-dimensional multi-fluid equations to understand the discharge pphysics of He-Xe discharge. The time deppendent distribution of the electron tempperature, densities of electrons, various ions and excited sppecies, and the effects fo the wall charge accumulated on the dielectric surface are obtained and comppared with the results of direct observation of time deppendent behavior of VUV and visible sppectra from single discharge cell observed using a gated, image intensified CCD to elucidate the discharge physics.

• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.167-174
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• 2008

The introduction of confocal microscopy makes it possible to observe the structural change of live neuronal cell. Neuro-degenerative disease, such as Alzheimer;s and Parkinson’s diseases are especially related to the morphological change of dendrite spine. That’s the reason for the study of segmentation and extraction from confocal microscope image. The difficulty comes from uneven intensity distribution and blurred boundary. Therefore, the image processing technique which can overcome these problems and extract the structural information should be suggested. In this paper, we propose robust structural information extracting technique with confocal microscopy images of dendrite in brain neurons. First, we apply the nonlinear diffusion filtering that enhance the boundary recognition. Second, we segment region of interest using iterative threshold selection. Third, we perform skeletonization based on Fast Marching Method that extracts centerline and boundary for analysing segmented structure. The result of the proposed method has been less sensitive to noise and has not been affected by rough boundary condition. Using this method shows more accurate and objective results.