A microscopic image classification system for high-throughput cell-cycle screening
Pham, Tuan D., Tran, Dat T., Zhou, X., and Wong, Stephen T.C. (2007) A microscopic image classification system for high-throughput cell-cycle screening. International Journal of Intelligent Computing in Medical Sciences and Image Processing, 1 (1). pp. 67-77.
PDF (Published Version)
Restricted to Repository staff only
Computerized high-throughput screening of cells using fluorescent microscopic imaging technology will tremendously help scientists gain the understanding of complex cellular processes that lead to drug discovery and disease treatment. Manual image analysis of cell images is very time-consuming, potentially inaccurate and poorly reproducible. Therefore the automation of cell-cycle screening, which has not been much explored, is critical for further biological downstream analysis. For such automation task, image classification of cell phases is considered to be most difficult. In this paper we present several computational models for the classification of cell nuclei in different mitotic phases recorded over a period of twenty-four hours at every fifteen minutes using time-lapse fluoresence microscopy. The experimental results have shown that the proposed methods are effective and can be useful for automating cell screening.
|Item Type:||Article (Refereed Research - C1)|
|Keywords:||pattern classification; image analysis; bioinformatics|
|Date Deposited:||28 Aug 2009 07:15|
|FoR Codes:||08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining @ 50%
08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing @ 50%
|SEO Codes:||89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890205 Information Processing Services (incl. Data Entry and Capture) @ 100%|