Cell Phase Classification Using Markov and Gaussian Mixture Models

Dat Tran, T Pham

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

Abstract

We present Gaussian mixture and Markov modelling methods for the computerized classification of cell nuclei in different mitotic phases. The methods were tested with the data set containing 379519 cells in 892 cell sequences for 5 phases extracted from real image sequences recorded at every fifteen minutes with a time-lapse fluorescence microscopy. The experimental results have shown that the proposed methods are effective and have potential for higher performance with better cellular feature extraction strategy.
Original languageEnglish
Title of host publicationProceedings of the 2005 Asia-Pacific Workshop on Visual Information Processing
EditorsH Yan, J S Jin, Z Liu, D S Yeung
Place of PublicationHong Kong
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages48-52
Number of pages5
ISBN (Print)962-442-278-8
Publication statusPublished - 2005
Event2005 Asia-Pacific Workshop on Visual Information Processing - , Hong Kong
Duration: 11 Dec 200513 Dec 2005

Conference

Conference2005 Asia-Pacific Workshop on Visual Information Processing
Country/TerritoryHong Kong
Period11/12/0513/12/05

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