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Optical cell tracking analysis using a straight-forward approach to minimize processing time for high frame rate
Wen Jun Seeto1, Elizabeth Ann Lipke1
1Department of Chemical Engineering, Auburn University, Auburn, Alabama 36849, USA.
The Review of Scientific Instruments
|April 3, 2016
Summary
A new optical cell tracking analysis (OCTA) system uses ImageJ and MATLAB to efficiently track rolling cells, overcoming common challenges in cell identification and proximity errors for faster, more accurate in vitro experiments.
Area of Science:
- Biomedical Engineering
- Cell Biology
- Image Analysis
Background:
- In vitro cell rolling analysis is crucial for understanding cellular behavior.
- Current methods face challenges with long computation times and cell-to-cell tracking errors, especially when cells are in close proximity.
Purpose of the Study:
- To develop a novel, efficient, and accurate rolling cell tracking system.
- To address limitations in computation time and cell-pair correlation in cell rolling data analysis.
Main Methods:
- Developed the Optical Cell Tracking Analysis (OCTA) system.
- Utilized ImageJ for initial cell identification in video frames.
- Employed custom MATLAB code for geometric and positional cell matching between frames to prevent tracking errors.
Main Results:
- The OCTA system significantly reduces computation time for high frame rate videos (e.g., <6 min for an 8000-frame video).
- Successfully minimized tracking errors caused by cells in close proximity or contact.
- Demonstrated effective tracking of endothelial colony forming cells (ECFCs) rolling under shear.
Conclusions:
- The OCTA system provides a sophisticated yet simple solution for accurate and rapid rolling cell tracking.
- This method enhances the analysis of cell rolling data by improving efficiency and reliability.
- OCTA simplifies the process, requiring only fundamental MATLAB knowledge after ImageJ-based cell identification.
