High-Throughput Method for Automated Colony and Cell Counting by Digital Image Analysis Based on Edge Detection

被引：99
作者：
Choudhry, Priya [1 ]
机构：
[1] CALTECH, Dept Chem, Pasadena, CA 91125 USA
来源：
PLOS ONE | 2016年 / 11卷 / 02期
关键词：
IN-VITRO; HEART MORPHOLOGY; EPITHELIAL-CELLS; LEAF MORPHOLOGY; STEM-CELLS; CULTURE; TOXICITY; LEUKEMIA; MODELS; GENE;
D O I：
10.1371/journal.pone.0148469
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：
Counting cells and colonies is an integral part of high-throughput screens and quantitative cellular assays. Due to its subjective and time-intensive nature, manual counting has hindered the adoption of cellular assays such as tumor spheroid formation in high-throughput screens. The objective of this study was to develop an automated method for quick and reliable counting of cells and colonies from digital images. For this purpose, I developed an ImageJ macro Cell Colony Edge and a CellProfiler Pipeline Cell Colony Counting, and compared them to other open-source digital methods and manual counts. The ImageJ macro Cell Colony Edge is valuable in counting cells and colonies, and measuring their area, volume, morphology, and intensity. In this study, I demonstrate that Cell Colony Edge is superior to other open-source methods, in speed, accuracy and applicability to diverse cellular assays. It can fulfill the need to automate colony/cell counting in high-throughput screens, colony forming assays, and cellular assays.
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页数：23
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