Automated segmentation and tracking of cells in time-lapse microscopy using watershed and mean shift

Xiaodong Yang, Houqiang Li, Xiaobo Zhou, Stephen Wong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

In this paper, we present a new method combining watershed and mean shift for segmentation and tracking of cancer cell nuclei in time-lapse fluorescence. First, we apply the watershed algorithm to segment the cells in each frame of the video sequence, including clustered cells. Second, mean shift method is employed to track each cell in its cycle progression. The proposed method can automatically segment and track all cells without any manual initialization. Experimental result shows that our method can detect almost all the touching cells and track them successfully, especially in the case of cell mitosis which is a difficult task using traditional methods such as snake and level set.

Original languageEnglish (US)
Title of host publicationProceedings of 2005 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2005
Pages533-536
Number of pages4
Volume2005
StatePublished - Dec 1 2005
Event2005 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2005 - Hong Kong, China
Duration: Dec 13 2005Dec 16 2005

Other

Other2005 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2005
CountryChina
CityHong Kong
Period12/13/0512/16/05

ASJC Scopus subject areas

  • Engineering(all)

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