Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins

• Published in: Journal of visualized experiments no. 117
• Main Authors: O'Brien, Jacob, Hayder, Heyam, Peng, Chun
• Format: Journal Article
• Language: English
• Published: United States MyJove Corporation 17-11-2016
• Subjects: Algorithms; Animals; Cell Count - methods; Cellular Biology; Humans; Image Processing, Computer-Assisted; Microscopy; Software
• ISSN: 1940-087X; 1940-087X
• DOI: 10.3791/54719

The National Institute of Health's ImageJ is a powerful, freely available image processing software suite. ImageJ has comprehensive particle analysis algorithms which can be used effectively to count various biological particles. When counting large numbers of cell samples, the hemocytometer presents a bottleneck with regards to time. Likewise, counting membranes from migration/invasion assays with the ImageJ plugin Cell Counter, although accurate, is exceptionally labor intensive, subjective, and infamous for causing wrist pain. To address this need, we developed two plugins within ImageJ for the sole task of automated hemocytometer (or known volume) and migration/invasion cell counting. Both plugins rely on the ability to acquire high quality micrographs with minimal background. They are easy to use and optimized for quick counting and analysis of large sample sizes with built-in analysis tools to help calibration of counts. By combining the core principles of Cell Counter with an automated counting algorithm and post-counting analysis, this greatly increases the ease with which migration assays can be processed without any loss of accuracy.