• Journal of Biosystems Engineering
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• v.38 no.1
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• pp.55-63
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• 2013

Purpose: The present study aimed at image processing methods for automatic cell pattern recognition and morphological analysis for tissue engineering applications. The primary aim was to ascertain the novel algorithm of adaptive brightness correction from microscopic images for use as a potential image analysis. Methods: General microscopic image of cells has a minor problem which the central area is brighter than edge-area because of the light source. This may affect serious problems to threshold process for cell-number counting or cell pattern recognition. In order to compensate the problem, we processed to find the central point of brightness and give less weight-value as the distance to centroid. Results: The results presented that microscopic images through the brightness correction were performed clearer than those without brightness compensation. And the classification of mixed cells was performed as well, which is expected to be completed with pattern recognition later. Beside each detection ratio of hBMSCs and HeLa cells was 95% and 92%, respectively. Conclusions: Using this novel algorithm of adaptive brightness correction could control the easier approach to cell pattern recognition and counting cell numbers.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.603-604
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• 2010

본 연구는 이미지 필터링 효과를 적용한 이미지들을 3D tomogram으로 만들었을 때 어느 정도의 효과적인 복원이 가능하고 또 어떤 해상도의 필터를 사용했을 때 더 나은 결과를 얻어 낼 수 있는 지 확인하기 위해 진행하였다. 전자현미경으로 2D tilted image들을 찍는 과정에는 고전압의 사용으로 인한 다소의 오류들이 발생한다. 따라서 이러한 오류를 상쇄시키고 3D tomogram의 질적 향상을 위하여 Gaussian low-pass filtering을 사용하였다. 또한 Gaussian low-pass filtering 내에서도 어떤 해상도 값의 필터링을 사용해야 더 나은 결과를 얻을 수 있는 지 확인하였다.

• Journal of ILASS-Korea
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• v.25 no.1
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• pp.15-20
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• 2020

This study aims to investigate injection rate and microscopic spray characteristics of diesel fuel containing fine air bubble (FBD). fine bubble was generated by cavitation theory using bubble generator. Fuel spray was injected into constant volume chamber and visualized by high speed camera. The injection rate data was acquired with bosch tube method. Injection rate of finebubble diesel was very similar with that of diesel. It showed slightly faster injection start by 5 ㎲ attributed to the low viscosity characteristics. In microscopic spray visualization, fine bubble diesel spray showed unsymmetric spray shape compared with diesel spray. It also showed very vigorous spray atomization performance during initial spray development. Improved atomization was also attributed to the low viscosity and surface tension of finebubble diesel fuel.

• Applied Microscopy
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• v.47 no.2
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• pp.75-76
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• 2017

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.3
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• pp.224-230
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• 2002

In this paper, a counting algorithm hybridized with an adaptive automatic thresholding method based on Otsu's method and the algorithm that elongates markers obtained by the well-known watershed algorithm is proposed to enhance the exactness of the microcell counting in microscopic images. The proposed counting algorithm can be stated as follows. The transformed full image captured by CCD camera set up at microscope is divided into cropped images of m$\times$n blocks with an appropriate size. The thresholding value of the cropped image is obtained by Otsu's method and the image is transformed into binary image. The microbial cell images below prespecified pixels are regarded as noise and are removed in tile binary image. The smoothing procedure is done by the area opening and the morphological filter. Watershed algorithm and the elongating marker algorithm are applied. By repeating the above stated procedure for m$\times$n blocks, the m$\times$n segmented images are obtained. A superposed image with the size of 640$\times$480 pixels as same as original image is obtained from the m$\times$n segmented block images. By labeling the superposed image, the counting result on the image of microbial cells is achieved. To prove the effectiveness of the proposed mettled in counting the microbial cell on the image, we used Acinetobacter sp., a kind of ammonia-oxidizing bacteria, and compared the proposed method with the global Otsu's method the traditional watershed algorithm based on global thresholding value and human visual method. The result counted by the proposed method shows more approximated result to the human visual counting method than the result counted by any other method.

• Biomedical Science Letters
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• v.11 no.1
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• pp.31-36
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• 2005

To evaluate the magnetic resonance imaging and electron microscopic findings of the hyperacute stage of cerebral fat embolism in cats and the time needed for the development of vasogenic edema. Magnetic resonance imaging was performed at 30 minutes (group 1, n=9) and at 30 minutes and 1, 2, 4, and 6 hours after embolization with triolein (group 2, n= 10). As a control for group 2, the same acquisition was obtained after embolization with polyvinyl alcohol particles (group 3, n=5). Electron microscopic examination was done in all cats. In group 1, the lesions were iso- or slightly hyperintense on T2-weighted (T2W) and diffusion-weighted (DWIs) images, hypointense on the apparent diffusion coefficient (ADC) map image, and markedly enhanced on the gadolinium-enhanced T1-weighted images (Gd-T1WIs). In group 2 at 30 minutes, the lesions were similar to those in group 1. Thereafter, the lesions became more hyperintense on T2WIs and DWIs and more hypoinfense on the ADC map image. In group 3, the lesions showed mild hyperintensity on T2WIs at 6 hours but hypointensity on the ADC map image from 30 minutes, with a tendency toward a greater decrease over time. Electron microscopic findings revealed discontinuity of the capillary endothelial wall, perivascular and interstitial edema, and swelling of glial and neuronal cells in groups 1 and 2. The lesions were hyperintense on T2WIs and DWIs, hypointense on the ADC map image, and enhanced on Gd-T1WIs. On electron microscopy, the lesions showed cytotoxic and vasogenic edema with disruption of the blood-brain barrier.

• Bulletin of the Korean Chemical Society
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• v.28 no.3
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• pp.391-396
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• 2007

The three-dimensional structure of an inorganic crystal, CaMoO4 (space group I 41/a, a = 5.198(69) A and c = 11.458(41) A), was determined by electron crystallography utilizing a high voltage electron microscope. An initial structure of CaMoO4 was determined with 3-D electron diffraction patterns. This structure was refined by crystallographic image processing of high resolution TEM images. X-ray crystallography of the same material was performed to evaluate the accuracy of the TEM structure determination. The cell parameters of CaMoO4 determined by electron crystallography coincide with the X-ray crystallography result to within 0.033-0.040 A, while the atomic coordinates were determined to within 0.072 A.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.77-82
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• 2001

An intelligent road transport management system focused on microscopic, real-time traffic signal control is proposed. Referring to the development of those systems in Japan, extensive use of image traffic detectors observing the movement of vehicles inside intersections, and direct data exchange between the signal controllers of neighboring intersections are newly assumed. On site investigation of five intersections in Japan or in Malaysia shows the possibility of effective information provision and simple algorithm for solving heavy congestion, as well as easy installation.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1545-1546
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• 2008

In this study, an image processing method with FRANSAC(Fuzzy RANSAC) is presented and discussed for the development of a microscopic gap measuring algorithm. Many problems in edge detection processing are mainly occurred by the illumination system. A serious problem is that the edge set of gap could include the error elements that have relatively larger error than normal. This problem leads to a incorrect measurement of gap. We present a gap measuring algorithm using FRANSAC[1] that is a representative robust estimation algorithm. FRANSAC is peformed by first categorizing all data into good sample set, bad sample set and vague sample set using a fuzzy classification and then sampling in only good sample set. Experimental results show that the presented gap measuring algorithm gives a higher accurate value of gap especially for the more noisy image data.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.2
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• pp.35-41
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• 2018

The analysis of plankton species distribution in sea or fresh water is very important in preserving marine ecosystem health. Since manual analysis is infeasible, many automatic approaches were proposed. They usually use images from in situ towed underwater imaging sensor or specially designed, lab mounted microscopic imaging system. Normally they assume that only single plankton is present in an image so that, if there is a clumping among multiple plankton of same species (homogeneous clumping) or if there are multiple plankton of different species scattered in an image (heterogeneous interspersion), they have a difficulty in recognition. In this work, we propose a deep learning based method that can detect and recognize individual plankton in images with homogeneous clumping, heterogeneous interspersion, or combination of both.