Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins

被引:78
作者
O'Brien, Jacob [1 ]
Hayder, Heyam [1 ]
Peng, Chun [1 ]
机构
[1] York Univ, Dept Biol, N York, ON M3J 1P3, Canada
来源
JOVE-JOURNAL OF VISUALIZED EXPERIMENTS | 2016年 / 117期
关键词
Cellular Biology; Issue; 117; image quantification; ImageJ; automated cell counting; particle counting; invasion; migration; hemocytometer; ImageJ plugin; ImageJ macro; MIGRATION; INVASION;
D O I
10.3791/54719
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
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页数:10
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