Cell phase identification using fuzzy Gaussian mixture models
Tran, Dat, Pham, Tuan, and Zhou, Xiaobo (2005) Cell phase identification using fuzzy Gaussian mixture models. Proceedings of the 2005 International Symposium on Intelligent Signal Processing and Communication Systems . 2005 International Symposium on Intelligent Signal Processing and Communication Systems , 13 - 16 December 2005, Hong Kong , pp. 465-468.
|PDF (Published Version) - Repository staff only - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader|
View at Publisher Website: http://dx.doi.org/10.1109/ISPACS.2005.15...
Fuzzy Gaussian mixture modeling method is proposed in this paper for the computerized classification of cell nuclei in different mitotic phases. A mixture of Gaussian distributions was used to represent the cell data in multi-dimensional cell feature space. Gaussian parameters were estimated using fuzzy c-means estimation. The method was tested with the data set containing 379519 cells in 5 phases extracted from real image sequences recorded at every fifteen minutes with a time-lapse fluorescence microscopy. Experimental results have shown that the proposed method is more effective than the Gaussian mixture modeling method.
|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 09:55|
|Last Modified:||12 Feb 2011 04:05|
Last 12 Months: 0
|Citation Counts with External Providers:|
Repository Staff Only: item control page