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

Area of Science:

• Cell Biology
• Bioimaging
• High-Throughput Screening

Background:

• Manual cell and colony counting is subjective and time-consuming, limiting the use of cellular assays in high-throughput screening.
• Assays like tumor spheroid formation require efficient and reliable counting methods for broader adoption.

Purpose of the Study:

• To develop an automated method for rapid and accurate counting of cells and colonies from digital images.
• To evaluate the performance of the developed ImageJ macro against other open-source methods and manual counts.

Main Methods:

• Development of an ImageJ macro named Cell Colony Edge.
• Development of a CellProfiler Pipeline named Cell Colony Counting.
• Comparative analysis of Cell Colony Edge, Cell Colony Counting, other open-source methods, and manual counting.

Main Results:

• The Cell Colony Edge ImageJ macro demonstrated superior speed and accuracy compared to other open-source digital methods.
• Cell Colony Edge is applicable to diverse cellular assays, including cell counting, colony forming assays, and tumor spheroid analysis.
• The macro enables measurement of cell and colony area, volume, morphology, and intensity.

Conclusions:

• The Cell Colony Edge ImageJ macro provides an automated, quick, and reliable solution for cell and colony counting.
• This tool addresses the need for automation in high-throughput screening and quantitative cellular assays.
• The macro's capabilities extend to detailed morphological and intensity measurements, enhancing its utility in biological research.