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An Automatic Indirect Immunofluorescence-Based Cell Segmentation, Counting and Recognition
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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 to scan a broad range of autoantibody entities and to describe them by distinct fluorescence patterns. Automatic inspection for fluorescence patterns in 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 location, segmentation, and recognition. In this paper, 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. This paper provides an automatic indirect immunofluorescence based cell segmentation and counting (AIICSC) system to segment and count the cells from an image taken under a fluorescence microscope. Moreover, in this paper, a recognition method is proposed to recognize the HEp-2 cells cut off from an IIF image.
|Appears in Collections:||資訊科學與工程學系所|
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