Cell counting is a fundamental technique in cell biology, crucial for understanding cellular processes such as proliferation, differentiation, and apoptosis. In the context of cancer research, proliferation assays are essential since cancer cells often exhibit uncontrolled growth and division. Counting cells can provide valuable insights into the efficacy of cancer treatments aimed at reducing cell numbers or inhibiting their growth. This Standard Operating Procedure (SOP) outlines a method for counting cells using ImageJ, a popular open-source image processing program. By quantifying cell numbers, researchers can assess the impact of various treatments on cell proliferation, contributing to the development of more effective cancer therapies
Open ImageJ and Load the Image
File
-> Open
.Convert the Image to 8-bit
Image
-> Type
-> 8-bit
to transform the image into an 8-bit grayscale image. This step is crucial for enhancing contrast and facilitating the identification of individual cells.Create a Region of Interest (ROI)
Analyze
-> Tools
-> ROI Manager
.Save
to store the ROI for future analysis.Duplicate the Image
Duplicate
to create a copy of the original image. This allows for processing without altering the original data.Set a Threshold
Image
-> Adjust
-> Threshold
(or use the shortcut Ctrl + Shift + T
) to apply a threshold. Adjusting the threshold helps to distinguish cells from the background.Apply the Watershed Algorithm
Process
-> Binary
-> Watershed
. The watershed algorithm helps to separate cells that are touching, making individual cells more distinguishable.Analyze Particles
Analyze
-> Analyze Particles
. This function quantifies and categorizes particles (cells) based on size and shape, effectively counting them.Check the Results
Measure Area of the Well and ROI
Analyze
-> Measure
(or use the shortcut Ctrl+M
).Calculate Cell Density
By following this SOP, researchers can accurately count and assess the density of cells in a given sample. This process is invaluable for experiments aimed at understanding cell proliferation, especially in the study of cancerous tissues where cell growth is a primary concern.
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