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Proceedings Paper

Segmentation and quantitative analysis of the living tumor cells using large-scale digital cell analysis system
Author(s): Fuxing Yang; Michael A. Mackey; Fiorenza Ianzini; Greg M. Gallardo; Milan Sonka
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Paper Abstract

The specific goal of our research is to develop automated methods for quantitative analysis of tumor cells from microscopic images. By segmenting living tumor cells, cell behavior under stress can be studied. Therefore, accurate acquisition and analysis of microscope images from living cell cultures are of utmost importance. If cell behavior can be studied through their life span, cell motility and shape changes can be quantified and analyzed in relation with the severity of induced stress. Consequently, cell responses to the environment can be quantitatively analyzed. The Large Scale Digital Cell Analysis System developed at the University of Iowa provides a capability for real-time cell image acquisition. In the work presented here, feasibility of fully automated living tumor cell segmentation is demonstrated allowing future quantitative cell studies. An automated method for identification of the cell boundaries in microscopy images is presented.

Paper Details

Date Published: 12 May 2004
PDF: 9 pages
Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); doi: 10.1117/12.536771
Show Author Affiliations
Fuxing Yang, Univ. of Iowa (United States)
Michael A. Mackey, Univ. of Iowa (United States)
Fiorenza Ianzini, Univ. of Iowa (United States)
Greg M. Gallardo, Univ. of Iowa (United States)
Milan Sonka, Univ. of Iowa (United States)


Published in SPIE Proceedings Vol. 5370:
Medical Imaging 2004: Image Processing
J. Michael Fitzpatrick; Milan Sonka, Editor(s)

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