An automated procedure for cell-phase imaging identification
Pham, Tuan D., Tran, Dat T., Zhou, Xiaobo., and Wong, Stephen T.C. (2005) An automated procedure for cell-phase imaging identification. Proceedings of the 18th Australian Joint Conference on Artificial Intelligence. 18th Australian Joint Conference on Artificial Intelligence , 5-9 December 2005, Sydney, NSW, Australia , pp. 52-59.
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Advances in fluorescent probing and microscopic imaging technology provide important tools for biomedical research in studying the structures and functions of cells and molecules. Such studies require the processing and analysis of huge amounts of image data, and manual image analysis is very time consuming, thus costly, and also potentially inaccurate and poorly reproducible. Stages of an automated cellular imaging analysis consist of segmentation, feature extraction, classification, and tracking of individual cells in a dynamic cellular population. Image classification of cell phases in a fully automatic manner presents the most difficult task of such analysis. We are particularly interested in combining several advanced computational, probabilistic, and fuzzy-set methods for the computerized classification of cell nuclei in different mitotic phases. We tested our proposed methods with real image sequences recorded over a period of twenty-four hours at every fifteen minutes with a time-lapse fluoresence microscopy, and the experimental results have shown that the proposed methods are effective for the identification task.
|Item Type:||Conference Item (Refereed Research Paper - E1)|
|FoR Codes:||08 INFORMATION AND COMPUTING SCIENCES > 0899 Other Information and Computing Sciences > 089999 Information and Computing Sciences not elsewhere classified @ 100%|
|SEO Codes:||89 INFORMATION AND COMMUNICATION SERVICES > 8999 Other Information and Communication Services > 899999 Information and Communication Services not elsewhere classified @ 100%|
|Deposited On:||08 Nov 2010 10:24|
|Last Modified:||12 Feb 2011 04:05|
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