• 제목, 요약, 키워드: Cell counting method

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A novel method for cell counting of Microcystis colonies in water resources using a digital imaging flow cytometer and microscope

  • Park, Jungsu;Kim, Yongje;Kim, Minjae;Lee, Woo Hyoung
    • Environmental Engineering Research
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    • v.24 no.3
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    • pp.397-403
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    • 2019
  • Microcystis sp. is one of the most common harmful cyanobacteria that release toxic substances. Counting algal cells is often used for effective control of harmful algal blooms. However, Microcystis sp. is commonly observed as a colony, so counting individual cells is challenging, as it requires significant time and labor. It is urgent to develop an accurate, simple, and rapid method for counting algal cells for regulatory purposes, estimating the status of blooms, and practicing proper management of water resources. The flow cytometer and microscope (FlowCAM), which is a dynamic imaging particle analyzer, can provide a promising alternative for rapid and simple cell counting. However, there is no accurate method for counting individual cells within a Microcystis colony. Furthermore, cell counting based on two-dimensional images may yield inaccurate results and underestimate the number of algal cells in a colony. In this study, a three-dimensional cell counting approach using a novel model algorithm was developed for counting individual cells in a Microcystis colony using a FlowCAM. The developed model algorithm showed satisfactory performance for Microcystis sp. cell counting in water samples collected from two rivers, and can be used for algal management in fresh water systems.

Pyramidal Deep Neural Networks for the Accurate Segmentation and Counting of Cells in Microscopy Data

  • Vununu, Caleb;Kang, Kyung-Won;Lee, Suk-Hwan;Kwon, Ki-Ryong
    • 한국멀티미디어학회논문지
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    • v.22 no.3
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    • pp.335-348
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    • 2019
  • Cell segmentation and counting represent one of the most important tasks required in order to provide an exhaustive understanding of biological images. Conventional features suffer the lack of spatial consistency by causing the joining of the cells and, thus, complicating the cell counting task. We propose, in this work, a cascade of networks that take as inputs different versions of the original image. After constructing a Gaussian pyramid representation of the microscopy data, the inputs of different size and spatial resolution are given to a cascade of deep convolutional autoencoders whose task is to reconstruct the segmentation mask. The coarse masks obtained from the different networks are summed up in order to provide the final mask. The principal and main contribution of this work is to propose a novel method for the cell counting. Unlike the majority of the methods that use the obtained segmentation mask as the prior information for counting, we propose to utilize the hidden latent representations, often called the high-level features, as the inputs of a neural network based regressor. While the segmentation part of our method performs as good as the conventional deep learning methods, the proposed cell counting approach outperforms the state-of-the-art methods.

생물학적 영상 분석을 위한 자동 모바일 셀 계수 시스템 (An Automatic Mobile Cell Counting System for the Analysis of Biological Image)

  • 서재준;전준철;이진성
    • 인터넷정보학회논문지
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    • v.16 no.1
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    • pp.39-46
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    • 2015
  • 본 논문에서는 모바일 환경에서 미세세포 영상으로부터 셀을 자동 검출하고 계수하는 자동화 방법을 제시하였다. 셀 카운팅은 생물학 또는 병리학적 영상분석에 있어서 매우 중요한 과정이다. 과거에는 셀 카운팅은 수동적인 방법으로 진행되어 매우 지루하고 많은 시간을 필요로 하는 작업이었다. 이에 더하여 수동 계수 방법은 정확한 카운팅 결과를 도출하는데 어려움이 있었다. 따라서, 정확하고 일관된 셀 검출과 카운팅 결과를 생물학적인 영상으로부터 획득하기 위해서는 자동화방법이 필요하다. 제안된 다단계 셀 계수방법은 배양된 세포영상으로부터 셀을 자동으로 분할하고 분할된 셀의 위상학적 분석을 통하여 셀을 라벨링 한다. 셀 카운팅의 정확도를 높이기 위하여 워터쉐드 알고리듬에 의하여 서로 덩어리로 뭉쳐진 셀을 서로 분리하고 모폴로지 연산을 통하여 영상으로부터 획득한 개별 셀의 형태를 개선한다. 제안된 시스템은 모바일 환경에서 사용될 수 있도록 개발되었다. 따라서 셀 영상은 모바일 폰의 카메라로 획득하며 미세세포의 통계학적인 분석 데이터는 유비쿼터스 환경의 모바일 장치에 의해 전송 된다. 실험을 통하여 수동으로 계수한 셀의 숫자와 제안된 방법에 의해 자동 카운팅 된 셀의 수를 비교한 결과 제안된 방법이 매우 효과적이고 정확한 결과를 제시한다는 사실을 입증하였다.

A Segmentation Method for Counting Microbial Cells in Microscopic Image

  • Kim, Hak-Kyeong;Lee, Sun-Hee;Lee, Myung-Suk;Kim, Sang-Bong
    • 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.

A New Cell Counting Method to Evaluate Anti-tumor Compound Activity

  • Wang, Xue-Jian;Zhang, Xiu-Rong;Zhang, Lei;Li, Qing-Hua;Wang, Lin;Shi, Li-Hong;Fang, Chun-Yan
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.8
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    • pp.3397-3401
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    • 2014
  • Determining cell quantity is a common problem in cytology research and anti-tumor drug development. A simple and low-cost method was developed to determine monolayer and adherent-growth cell quantities. The cell nucleus is located in the cytoplasm, and is independent. Thus, the nucleus cannot make contact even if the cell density is heavy. This phenomenon is the foundation of accurate cell-nucleus recognition. The cell nucleus is easily recognizable in images after fluorescent staining because it is independent. A one-to-one relationship exists between the nucleus and the cell; therefore, this method can be used to determine the quantity of proliferating cells. Results indicated that the activity of the histone deacetylase inhibitor Z1 was effective after this method was used. The nude-mouse xenograft model also revealed the potent anti-tumor activity of Z1. This research presents a new anti-tumor-drug evaluation method.

뉴럴 네트워크를 이용한 배터리 셀 SOC 추정 (Battery Cell SOC Estimation Using Neural Network)

  • 유경상;김호찬
    • 전기전자학회논문지
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    • v.24 no.1
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    • pp.333-338
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    • 2020
  • 본 논문은 역전파 뉴럴 네트워크(Back Propagation Neural Network; BPNN) 알고리즘을 이용한 배터리 셀의 잔존용량(State Of Charge; SOC) 추정 방법을 제안한다. 이를 위해 배터리 성능평가 시뮬레이터를 구현하고 다양한 온도에서의 충방전 실험을 통해 뉴럴 네트워크 학습에 필요한 입출력 데이터를 도출한다. 최종적으로 배터리의 SOC 추정 성능은 Matlab/Simulink 프로그램을 이용하여 Ah-counting에 의한 실험치와 비교를 통해 분석하고 오차율을 3% 미만으로 줄일 수 있음을 시뮬레이션을 통해 확인한다.

위성 TDMA 전송에서 가변타임스탬프 방식의 셀 지연변이 보상의 모델과 해석 (A Study on the Modeling and Analysis of Cell Delay Variation Compensation using Variable Timestamp Method in the Satellite TDMA Transmission)

  • 김정호;박진양
    • 한국컴퓨터산업학회논문지
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    • v.2 no.11
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    • pp.1395-1406
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    • 2001
  • 광범위한 지역의 서비스 영역을 지원하기 위하여 지상/위성 혼합망을 구성한다. 위성 TDMA가 ATM 접속에 따른 CDV 보상을 위하여 기존의 지상 CDV 보상기법이 적용되어 왔다. 기존의 타임 스탬프 방식과 셀 계수 방법의 단점을 지원하기 위하여 CDV 보상을 위한 새로운 가변 타임 스탬프 방식을 제안하였다. 본 제안된 방식에서 VBR 서비스를 표현하기 위해 지상국의 셀 입력 트래픽 모델을 위한 MMPP 모델로 선택하였다. 모의 실험을 통하여 VBR 서비스의 보상 능력이 셀 계수 방법과 비교할 때, 타임스탬프 수 Nts 가 증가할수록 CDV 보상능력은 증가하고 CDV 분포 폭이 줄어들었음을 알 수 있었다.

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Mechanical properties, Biodegradability and Biocompatibility of Coronary Bypass Artery with PCL Layer and PLGA/Chitosan Mats Using Electrospinning

  • Nguyen, Thi-Hiep;Min, Young-Ki;Yang, Hun-Mo;Song, Ho-Yeon;Lee, Byong-Taek
    • 한국재료학회:학술대회논문집
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    • pp.45.2-45.2
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    • 2009
  • A coronary graft fabricated from PLGA poly (lactic-co-glycolic acid) and chitosan electros puns deposited on poly caprolactone (PCL) electro spun tube. Mechanical properties of tube were evaluated through extruder machine depending on thickness of vessel wall. Biocompatible properties were evaluated by SEM morphology, amount of cell counting and MTT assay method for depending on culture days (1, 3, 5 days). MTT assay, counting cell and SEM morphology showed that cells were fast growth and immigration after 5 days. Biodegradability was monitored through loss weigh method for incubator days.

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수퍼 샘플링과 보간을 이용한 생물조직 영상의 면적 측정 (Area Measurement of Organism Image using Super Sampling and Interpolation)

  • 최선완;유숙현
    • 한국멀티미디어학회논문지
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    • v.17 no.10
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    • pp.1150-1159
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    • 2014
  • This paper proposes a method for extracting tissue cells from an organism image by an electron microscope and getting the whole cell number and the area from the cell. In general, the difference between the cell color and the background is used to extract tissue cell. However, there may be a problem when overlapped cells are seen as a single cell. To solve the problem, we split them by using cell size and curvature. This method has a 99% accuracy rate. To measure the cell area, we compute two areas, the inside and boundary of the cell. The inside is simply calculated by the number of pixels. The cell boundary is obtained by applying super sampling, linear interpolation, and cubic spline interpolation. It improves the error rate, 18%, 19%, and 120% respectively, in comparison to the counting method that counts a pixel area as 1.

Enzymatic Determination of Somatic Cells by Using Transparisation in Raw Milk

  • Lee, Bou-Oung;Xu, Wen-Ying;Chang, Oun-Ki;Jin, Tai-Hua
    • 한국축산식품학회지
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    • v.24 no.4
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    • pp.411-415
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    • 2004
  • The transparisation technology for milk and milk products could be applied widely and very importantly to various determination because transparisation can economize the cost and increase with precision in the milk payment system. Component of butanone or Triton in transparisation solvent would inhibit the growth of bacteria and method. Enzymatic determination of leucocytes were proposed to evaluate milk quality as mastitis in the milk payment system, this can be easily applied to simplify automation of the determation with the lowest investment cost in milk pay system. The significance of this technique, it can be used in the quality control of raw milk and milk products, milk payment system, and programming of national dairy project. Transparisation technology is used in somatic cell counting by enzymic methods. The range of deviation for this method is 16% in 74 samples. But the deviation is increased to 20% when the Infoss method is used. It is affected by the percentage of epithelial cells and white blood cells in somatic cells from different animals and the stages of aging. NAgase activity has an obvious correlation with white-blood cells in milk. In the case of mastitis the white-blood cells is 90-95% in somatic cells in milk, it is showing greater precision in measuring the state of mastitis. In conclusion the enzymic method of somatic cell counting is a relatively simple and easy method of measurement and can be easily practiced. And the importance of this method is also worth utilizing for indirect counting of Somatic cells by use of synthetic substrates to NAgase. In the future, with the further development of the research in this field, it will b possible to automatize the measurement.