• Journal of the Korean Society of Visualization
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• v.8 no.1
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• pp.46-52
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• 2010

In the present study, we employed the confocal laser scanning microscopy (CLSM) system to visualize the blood flow field with $1{\times}1{\mu}m^2$ spatial resolution. Based on the confocal microscopic image of red blood cells (RBCs), we performed the velocity vector field measurement and evaluated characteristics of cell migration from the cell depleted layer thickness calculation. The rat and mouse's blood were supplied into a micro glass tubes in vitro. The line scanning rate of confocal microscopy was 15 kHz for a $500{\times}500$ pixels image. As a result, the red blood cell itself can be used as a tracer directly without any kind of invasive tracer particle to get the velocity vector field of blood flow by performing particle image velocimetry (PIV) technique.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.159-166
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• 2021

In order to analyze cell images, accurate segmentation of each cell is indispensable. However, the reality is that accurate cell image segmentation is not easy due to various noises, dense cells, and inconsistent shape of cells. Therefore, in this paper, we propose an algorithm that combines marker-based watershed segmentation and ellipse fitting method for glioblastoma cell segmentation. In the proposed algorithm, in order to solve the over-segmentation problem of the existing watershed method, the marker-based watershed technique is primarily performed through "seeding using local minima". In addition, as a second process, the concave point search using ellipse fitting for final segmentation based on the connection line between the concave points has been performed. To evaluate the performance of the proposed algorithm, we compared three algorithms with other algorithms along with the calculation of segmentation accuracy, and we applied the algorithm to other cell image data to check the generalization and propose a solution.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.670-673
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• 2002

This paper proposes a digital algorithm for gray-scale/color image segmentation of real-time video signals and a cell-network-based implementation architecture in state-of-the-art CMOS technology. Through extrapolation of design and simulation results we predict that about 300$\times$300 pixels can be integrated on a chip at 100nm CMOS technology, realizing very high-speed segmentation at about 1600sec per color image. Consequently real-time color-video segmentation will become possible in near future.

• Korean Journal of Clinical Laboratory Science
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• v.38 no.3
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• pp.203-207
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• 2006

The purpose of this study was to develop discriminant analysis models for predicting cervical normal/dysplasia case diagnoses using cytometric features derived from the digital image analysis of cell monolayers. The database consisted of 19 cases diagnosed either as normal (n=5), moderate dysplasia (n=7), severe dysplasia (n=7) on monolayer preparations. We studied the nuclear and cytoplasmic characteristics of cells in the normal, moderate dysplasia and severe dysplasia on cervical samples. The morphometric parameters selected for the analysis were nuclear/cytoplasmic ratio and the nuclear variations measured by image analysis on normal and precancerous lesions of cervical smears; several shape factors; area; perimeter; maximal, minimal and equivalent circle diameters. The results showed that the dysplasia samples exhibited changes in both cellular and nuclear form and size but lacked substantial differences in the tumor grades. The coefficient of nuclear variation is as follows to normal cell $21.8{\pm}3.2%$, moderate dysplasia $33.5{\pm}6.1%$, severe dysplasia $27.7{\pm}5.8$ of cervical smears.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.71-78
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• 2019

Most 3D displays that are currently in the market adopt the binocular disparity method creating a different image for the left and right eye for a 3 dimensional effect. However, commercialized 3D image output devices lack in performance making it uncomfortable for the viewer and restrict the viewer to certain positions. In this paper, we propose a single-cell polarized lens type stereoscopic system which has a smaller viewing angle and reduced crosstalk, with improved light penetration compared to existing double-cell structures; and analyzed the single-cell polarized lens type stereoscopic system properties, and conducted an effect analysis of performance improvement compared to the dual-cell type. Results showed that the single-cell type had a 25% improved performance, and the 3D crosstalk index which is an important index for quality characteristics of stereoscopic systems, increased over about 37%, compared to the dual-cell type.

• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1326-1335
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• 2021

As part of the cell division method, we proposed a method for segmenting images generated by topography microscopes through deep learning-based feature generation and graph segmentation. Hybrid vector shapes preserve the overall shape and boundary information of cells, so most cell shapes can be captured without any post-processing burden. NIH-3T3 and Hela-S3 cells have satisfactory results in cell description preservation. Compared to other deep learning methods, the proposed cell image segmentation method does not require postprocessing. It is also effective in preserving the overall morphology of cells and has shown better results in terms of cell boundary preservation.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.47-54
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• 2019

This study is concerned with the mechanism and structure of an optical microscope and an automatic multi-focus algorithm for automatically selecting sharp images from multiple foci of a cell. To obtain precise cell images quickly, a z-axis actuator with a resolution of $0.1{\mu}m$ was designed to control an optical microscope Moreover, a lighting control system was constructed to select the color and brightness of light that best suit the object being viewed. Cell images are captured by the instrument and the sharpness of each image is determined using Gaussian and Laplacian filters. Next, cubic spline interpolation and peak detection algorithms are applied to automatically find the most vivid points among multiple images of a single object. A cancer cell imaging experiment using propidium iodide staining confirmed that a sharp multipoint image can be obtained using this microscope. The proposed system is expected to save time and effort required to extract suitable cell images and increase the convenience of cell analysis.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.103-113
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• 2019

Motivation: Polymerized actin-based cytoskeletal structures are crucial in shape, dynamics, and resilience of a cell. For example, dynamical actin-containing ruffles are located at leading edges of cells and have a significant impact on cell motility. Other filamentous actin (F-actin) bundles, called stress fibers, are essential in cell attachment and detachment. For this reason, their mechanistic understanding provides crucial information to solve practical problems related to cell interactions with materials in tissue engineering. Detecting and counting actin-based structures in a cellular ensemble is a fundamental first step. In this research, we suggest a new method to characterize F-actin wrapping fibers from confocal fluorescence image stacks. As fluorescently labeled F-actin often envelope the fibers, we first propose to segment these fibers by diminishing an energy based on maximum flow and minimum cut algorithm. The actual actin is detected through the use of bilateral filtering followed by a thresholding step. Later, concave actin bundles are detected through a graph-based procedure that actually determines if the considered actin filament is enclosing the fiber.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.1411-1412
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• 2013

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.3 s.258
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• pp.380-387
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• 2007

We carried out an image analysis of living cells forming their contacts at the bottom of the cell culturing substrate. In order to visualize the contact area selectively, we adopted total-internal-reflection-fluorescence (TIRF) method, which can illuminate the specimen volume within only several hundred nano-meters above the substrate. From the fluorescent intensity of the TRF image, we could calculate the distance of the cell surface from the substrate. As a result, we visualized the origin of cell contacts, their movements, and the change of cell-contact type from the close-contact into focal-contact with information of its vertical displacement representing the temporal evolution process of the three-dimensional cell-surface-profile near the contact area during this metamorphosis.