An Automatic Indirect Immunofluorescence Cell Segmentation System

Author:

Chan Yung-Kuan1ORCID,Huang Der-Chen2,Liu Kuo-Ching3,Chen Rong-Tai2,Jiang Xiaoyi4ORCID

Affiliation:

1. Department of Management Information Systems, National Chung Hsing University, Taichung 402, Taiwan

2. Department of Computer Science and Engineering, National Chung Hsing University, Taichung 402, Taiwan

3. Department of Science and Biotechnology, China Medical University, Taichung 402, Taiwan

4. Department of Computer Science, University of Munster, 48149 Münster, Germany

Abstract

Indirect immunofluorescence (IIF) with HEp-2 cells has been used for the detection of antinuclear autoantibodies (ANA) in systemic autoimmune diseases. The ANA testing allows us to scan a broad range of autoantibody entities and to describe them by distinct fluorescence patterns. Automatic inspection for fluorescence patterns in an IIF image can assist physicians, without relevant experience, in making correct diagnosis. How to segment the cells from an IIF image is essential in developing an automatic inspection system for ANA testing. This paper focuses on the cell detection and segmentation; an efficient method is proposed for automatically detecting the cells with fluorescence pattern in an IIF image. Cell culture is a process in which cells grow under control. Cell counting technology plays an important role in measuring the cell density in a culture tank. Moreover, assessing medium suitability, determining population doubling times, and monitoring cell growth in cultures all require a means of quantifying cell population. The proposed method also can be used to count the cells from an image taken under a fluorescence microscope.

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

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