Conference proceeding
Segmentation and quantitative analysis of the living tumor cells using large-scale digital cell analysis system
Proceedings of SPIE, Vol.5370(1), pp.1755-1763
Medical Imaging 2004: Image Processing
05/12/2004
DOI: 10.1117/12.536771
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.
Details
- Title: Subtitle
- Segmentation and quantitative analysis of the living tumor cells using large-scale digital cell analysis system
- Creators
- Fuxing Yang - University of IowaMichael A Mackey - University of IowaFiorenza Ianzini - University of IowaGreg M Gallardo - University of IowaMilan Sonka - University of Iowa
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of SPIE, Vol.5370(1), pp.1755-1763
- Conference
- Medical Imaging 2004: Image Processing
- DOI
- 10.1117/12.536771
- ISSN
- 0277-786X
- Language
- English
- Date published
- 05/12/2004
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Radiation Oncology; Fraternal Order of Eagles Diabetes Research Center; Injury Prevention Research Center; Ophthalmology and Visual Sciences
- Record Identifier
- 9984186601602771
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