TY - JOUR
T1 - Automated Bright Field Segmentation of Cells and Vacuoles Using Image Processing Technique
AU - Chiang, Pei Ju
AU - Wu, Shao Ming
AU - Tseng, Min Jen
AU - Huang, Pin Jie
N1 - Funding Information:
We are grateful for the statistical advice provided by Malcolm Koo at the Department of Medical Research, Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Taiwan. This work was supported by the Ministry of Science and Technology of Taiwan, ROC, under grant no MOST 103-2221-E-194-042.
Funding Information:
Grant sponsor: Ministry of Science and Technology, Taiwan, Grant number- MOST 103-2221-E-194 -042 *Correspondence to: Pei-Ju Chiang, Department of Mechanical Engineering and Advanced Institute of Manufacturing with High-Tech Innovations, National Chung Cheng University, No. 168, Sec. 1, University Rd, Minhsiung, Chiayi 62102, Taiwan, ROC. Email: chiang.peiju@gmail.com
Publisher Copyright:
© 2018 International Society for Advancement of Cytometry
PY - 2018/10
Y1 - 2018/10
N2 - Understanding the mechanisms and other variants of programmed cell death will help provide deeper insight into various disease processes. Although complex procedures are required to distinguish each type of cell death, the formation of vacuoles is one of the important features in some process of cell death under different conditions. Thus, monitoring and counting the number of vacuoles and the ratio of cells with vacuoles is a commonly used method to indicate and quantify the efficacy of the therapy. Several studies have shown that image processing can provide a quick, convenient and precise mean of performing cell detection. Hence, this study uses an image processing technique to detect and quantify vacuolated cells without the need for dyes. The system both counts the number of vacuolated cells and determines the ratio of cells with vacuoles. The performance of the proposed image processing system was evaluated using 38 images. It has been shown that a strong correlation exists between the automated counts and the manual counts. Furthermore, the absolute percentage errors between automated counts and manual counts for cell detection and vacuolated cell detection using data pooled from all images are 3.61 and 3.33%, respectively. A user-friendly graphical user interface (GUI) is also developed and freely available for download, providing researchers in biomedicine with a more convenient instrument for vacuolization analysis.
AB - Understanding the mechanisms and other variants of programmed cell death will help provide deeper insight into various disease processes. Although complex procedures are required to distinguish each type of cell death, the formation of vacuoles is one of the important features in some process of cell death under different conditions. Thus, monitoring and counting the number of vacuoles and the ratio of cells with vacuoles is a commonly used method to indicate and quantify the efficacy of the therapy. Several studies have shown that image processing can provide a quick, convenient and precise mean of performing cell detection. Hence, this study uses an image processing technique to detect and quantify vacuolated cells without the need for dyes. The system both counts the number of vacuolated cells and determines the ratio of cells with vacuoles. The performance of the proposed image processing system was evaluated using 38 images. It has been shown that a strong correlation exists between the automated counts and the manual counts. Furthermore, the absolute percentage errors between automated counts and manual counts for cell detection and vacuolated cell detection using data pooled from all images are 3.61 and 3.33%, respectively. A user-friendly graphical user interface (GUI) is also developed and freely available for download, providing researchers in biomedicine with a more convenient instrument for vacuolization analysis.
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U2 - 10.1002/cyto.a.23595
DO - 10.1002/cyto.a.23595
M3 - Article
C2 - 30230197
AN - SCOPUS:85053695444
VL - 93
SP - 1004
EP - 1018
JO - Cytometry. Part A : the journal of the International Society for Analytical Cytology
JF - Cytometry. Part A : the journal of the International Society for Analytical Cytology
SN - 1552-4922
IS - 10
ER -