Integrated algorithms for image analysis and classification of nuclear division for high-content cell-cycle screening
Pham, Tuan D., Tran, Dat T., Zhou, Xiaobo, and Wong, Stephen T.C. (2006) Integrated algorithms for image analysis and classification of nuclear division for high-content cell-cycle screening. International Journal of Computational Intelligence and Applications, 6 (1). pp. 21-43.
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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 poor reproducibility. In this paper, we present and combine 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 fluorescence microscopy. The experimental results have shown that the proposed methods are effective for the task of classification.
|Item Type:||Article (Refereed Research - C1)|
|Keywords:||bioimaging; classification; microscopic imaging; nuclear division; pattern classification; probability; fuzzy algorithms; computational methods|
|SEO Codes:||92 HEALTH > 9202 Health and Support Services > 920203 Diagnostic Methods @ 34%|
92 HEALTH > 9204 Public Health (excl. Specific Population Health) > 920412 Preventive Medicine @ 33%
92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920102 Cancer and Related Disorders @ 33%
|Deposited On:||07 Dec 2009 09:03|
|Last Modified:||02 Nov 2012 09:10|
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