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Proceedings Paper

Cell segmentation for division rate estimation in computerized video time-lapse microscopy
Author(s): Weijun He; Xiaoxu Wang; Dimitris N. Metaxas; Robin Mathew; Eileen White
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Paper Abstract

The automated estimation of cell division rate plays an important role in the evaluation of a gene function in high throughput biomedical research. Using Computerized Video Time-Lapse (CVTL) microcopy , it is possible to follow a large number of cells in their physiological conditions for several generations. However analysis of this large volume data is complicated due to cell to cell contacts in a high density population. We approach this problem by segmenting out cells or cell clusters through a learning method. The feature of a pixel is represented by the intensity and gradient information in a small surrounding sub-window. Curve evolution techniques are used to accurately find the cell or cell cluster boundary. With the assumption that the average cell size is the same in each frame, we can use the cell area to estimate the cell division rate. Our segmentation results are compared to manually-defined ground truth. Both recall and precision measures for segmentation accuracy are above 95%.

Paper Details

Date Published: 8 February 2007
PDF: 8 pages
Proc. SPIE 6431, Multimodal Biomedical Imaging II, 643109 (8 February 2007); doi: 10.1117/12.717590
Show Author Affiliations
Weijun He, Rutgers Univ. (United States)
Xiaoxu Wang, Rutgers Univ. (United States)
Dimitris N. Metaxas, Rutgers Univ. (United States)
Robin Mathew, Ctr. for Advanced Biotechnology and Medicine, Rutgers Univ. (United States)
Eileen White, Ctr. for Advanced Biotechnology and Medicine, Rutgers Univ. (United States)

Published in SPIE Proceedings Vol. 6431:
Multimodal Biomedical Imaging II
Fred S. Azar, Editor(s)

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