• Journal of KIISE
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• v.42 no.10
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• pp.1239-1246
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• 2015

Cell counting is extensively used to analyze cell growth in biomedical research, and as a result automated cell counting methods have been developed to provide a more convenient and means to analyze cell growth. However, there are still many challenges to improving the accuracy of the cell counting for cells that proliferate abnormally, divide rapidly, and cluster easily, such as cancer cells. In this paper, we present an automated cell counting method for HeLa cells, which are used as reference for cancer research. We recognize and classify the morphological conditions of the cells by using a cell segmentation algorithm based on cell membrane extraction, and we then apply a cell back-tracking algorithm to improve the cell counting accuracy in cell clusters that have indistinct cell boundary lines. The experimental results indicate that our proposed segmentation method can identify each of the cells more accurately when compared to existing methods and, consequently, can improve the cell counting accuracy.

• Journal of Industrial Technology
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• v.29 no.A
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• pp.61-65
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• 2009

A colony counting on a petri-dish is a laborious task in microbiology fields that automated counting systems are needed. But lots of such systems are high price that majorities of labs rely on the manual counting and it is a time consuming and laborious job. In this study, an attempt was made to select the relative atmospheric correction method for the water quality factors extraction from the satellite image data. And also, the time-series analysis of the water quality factors was performed by using the multi-temporal image data. The result shows that the proposed method can be commercialized with low prices.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1973-1978
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• 2011

The almost existing automated pedestrian systems are not well suited to the task of counting pedestrians in outdoor environments, and little is known about their effectiveness and accuracy. In this paper, we proposed a system to count pedestrians in crowds from a outdoor camera. And we describes pedestrian counting which detects and count moving people based pixel counting. This method is intended to estimates the number of people in outdoor environment.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.9-9
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• 2000

Accurate counting and packaging pills is one of the most fundamental works of the pharmaceutical industry. But it is so labor consuming and very hard to be automated. As the pharmaceutical industry is growing bigger, the need of counting and packaging automation is increasing to obtain effective mass production. Precise and quick sensing is required in the counting and processing of quickly dropping pills to improve the productivity. There are many trials for this automation and automatic machine. But the performance of the existing counting machine varies with the size, shape and the dispersion degree of pills In this research, authors design the counting and packing machine of medicinal pills that is more accurate and highly trustworthy After getting analog signal from optical sensor, pill passage is discriminated from chosen characteristic feature using microprocessor.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.9
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• pp.810-815
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• 2005

As the pharmaceutical industry grows and becomes more competitive, the need of automation increases to establish effective mass production and to maintain consistent quality control. Accurate counting and packing of medicinal pills is one of the most essential processes that the automation can benefit. In conventional automated counting and packing processes, the performance of counting process varies with the size, the shape and the dispersion degree of pills. In this research, the authors developed a new pill-counting algorithm based on carefully analyzed characteristics of the pill-drop behavior. Also a new scheme for the packing of an exact number of pills has been implemented. A pill counting and packing machine with the new pill-counting algorithm and the new packing scheme has been constructed and put in an actual production line. To achieve precise and quick sensing of pills dropping at a high speed from the preceding processors, the machine uses non-contact photo sensors. Experimental results from the actual process using the machine are included to verify the effectiveness of the proposed algorithm and the machine.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.4
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• pp.652-657
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• 2013

In this study, we developed a counting method for non-contact ID cards using an optical fiber displacement sensor instead of the traditionally used friction counting method. The proposed method has the advantage of high speed and automated measurement. For counting non-contact ID cards, an H-type optical fiber sensor, jig part, and counting program are developed separately to build the system and adjust it. Through the experimental test results, it was confirmed that counting is possible with one type of international ID card and one type of financial security card based on ISO7810. Furthermore, by applying the proposed method to 100 ID cards 100 times repeatedly, it was confirmed that it has high accuracy and an error ratio of 0%. We experimentally demonstrated that the proposed counting method for non-contact ID cards using an optical fiber displacement sensor can perform measurements with high accuracy and high speed.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.24 no.4
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• pp.484-491
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• 2014

Objectives: An image processing program for asbestos fibers analyzing the gradient components and partial linearity was developed in order to accurately segment fibers. The objectives were to increase the accuracy of counting through the formulation of the size and shape of fibers and to guarantee robust fiber detection in noisy backgrounds. Methods: We utilized samples mixed with sand and sepiolite, which has a similar structure to asbestos. Sample concentrations of 0.01%, 0.05%, 0.1%, 0.5%, 1%, 2%, and 3%(w/w) were prepared. The sand used was homogenized after being sieved to less than $180{\mu}m$. Airborne samples were collected on MCE filters by utilizing a personal pump with 2 L/min flow rate for 30 minutes. We used the NIOSH 7400 method for pre-treating and counting the fibers on the filters. The results of the NIOSH 7400 method were compared with those of the image processing program. Results: The performance of the developed algorithm, when compared with the target images acquired by PCM, showed that the detection rate was on average 88.67%. The main causes of non-detection were missing fibers with a low degree of contrast and overlapping of faint and thin fibers. Also, some duplicate countings occurred for fibers with breaks in the middle due to overlapping particles. Conclusions: An image detection algorithm that could increase the accuracy of fiber counting was developed by considering the direction of the edge to extract images of fibers. It showed comparable results to PCM analysis and could be used to count fibers through real-time tracking by modeling a branch point to graph. This algorithm can be utilized to measure the concentrations of asbestos in real-time if a suitable optical design is developed.

• Korean Chemical Engineering Research
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• v.61 no.2
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• pp.247-257
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• 2023

Precise counting of cell number stands in important position within clinical and research laboratories. Conventional methods such as hemocytometer, migration/invasion assay, or automated cell counters have limited in analytical time, cost, and accuracy., which needs an alternative way with time-efficient in-situ approach to broaden the application avenue. Here, we present simple coding-based cell counting method using image analysis tool, freely available image software (ImageJ). Firstly, we encapsulated RFP-expressing bacteria in a droplet using microfluidic device and automatically performed fluorescence image-based analysis for the quantification of cell numbers. Also, time-lapse images were captured for tracking the change of cell numbers in a droplet containing different concentrations of antibiotics. This study confirms that our approach is approximately 15 times faster and provides more accurate number of cells in a droplet than the external analysis program method. We envision that it can be used to the development of high-throughput image-based cell counting analysis.

• Applied Microscopy
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• v.51
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• pp.4.1-4.12
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• 2021

Fluorescence in situ hybridization (FISH) is a technique to visualize specific DNA/RNA sequences within the cell nuclei and provide the presence, location and structural integrity of genes on chromosomes. A confocal Whole Slide Imaging (WSI) scanner technology has superior depth resolution compared to wide-field fluorescence imaging. Confocal WSI has the ability to perform serial optical sections with specimen imaging, which is critical for 3D tissue reconstruction for volumetric spatial analysis. The standard clinical manual scoring for FISH is labor-intensive, time-consuming and subjective. Application of multi-gene FISH analysis alongside 3D imaging, significantly increase the level of complexity required for an accurate 3D analysis. Therefore, the purpose of this study is to establish automated 3D FISH scoring for z-stack images from confocal WSI scanner. The algorithm and the application we developed, SHIMARIS PAFQ, successfully employs 3D calculations for clear individual cell nuclei segmentation, gene signals detection and distribution of break-apart probes signal patterns, including standard break-apart, and variant patterns due to truncation, and deletion, etc. The analysis was accurate and precise when compared with ground truth clinical manual counting and scoring reported in ten lymphoma and solid tumors cases. The algorithm and the application we developed, SHIMARIS PAFQ, is objective and more efficient than the conventional procedure. It enables the automated counting of more nuclei, precisely detecting additional abnormal signal variations in nuclei patterns and analyzes gigabyte multi-layer stacking imaging data of tissue samples from patients. Currently, we are developing a deep learning algorithm for automated tumor area detection to be integrated with SHIMARIS PAFQ.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2493-2499
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• 2011

With growth of nano-bio industry, it is of significant importance to develop an automated system to exploit cell behaviors, including migration, mitosis, apoptosis, shape deformation of individual cells and their interactions among cells in the process of cell growth. In this paper, we proposed preprocessing techniques, a classification method which classifies clusters (overlapping multiple cells) from cells and an automated method which counts the number of cells and clusters in order to analyze 2D or 3D deformations of the cells in the real-time images from microscope in the cell culture. We conducted the 3T3 cell images taken from each thirty-minute interval. It showed the average 99.8% accuracy automatically for separating cells and clusters.