Use ImageJ to calculate the number of cells, nuclei and types of shapes

Sample image and/or code

25 November 2019_STL KO1_ch00.tif (290.2 KB)
25 November 2019_STL KO1_ch01.tif (290.2 KB)


KO stands for Knock out.
STL: Solanum tuberosum lectin

This is part of my final year project, where I am studying breast cancer cells stained in the laboratory and have been studied using confocal microscopy.

My job is to count how many cells they are. So, counting the number of nuclei.
Comment on the shape of the cells- i.e. if they are rounded or elongated.

The images that were provided are two sets of stains, we’ve got the blue stain, the nuclei, and then the same cells have been stained with protein that is labelled green, called a lectin—this stains carbohydrate.

This project’s is to find out if both data set from wild type and knock out in experiment 1 and in experiment 2 shows any changes in the cell shape and type, and how they look morphology and if there is a change in the glycosylation.

Analysis goals

I have looked at the resources available from the amazing Image Analysis with ImageJ/FIJI Workshop | 5.17.17 on Vimeo

I am unsure how, to begin with, mine.

  • What information are you interested in getting from this image?

I am interested in knowing the number of cells, intensity, shapes, total area, mean, circularity, solidity, and other relevant data that might be helpful., but for now, the mentioned things should suffice.

I would love to create a script so I can do a batch process.


  • What stops you from proceeding?
  • What have you tried already?

I have done brightness, contrast…

But all of these looked weird to me compared to the desired format. I also have to label it

The above image is a screenshot from a paper that is different from mine, and I have been told it should look like that.

After doing a practice, I got so confused.

Help is much appreciated, and apology for any inconvenient that I have caused.

could anyone help me with this :smiley:

It seems that there is some confusion on images and channels. Rather than opening one of your images by drag-and-drop (onto the ImageJ bar), try using the Bio-Formats importer (in Fiji: Plugins → Bio-Formats → Bio-Formats Importer). In the Import Options dialog, select Color mode: Composite.

Despite being labeled with the suffixes _ch00.tif and _ch01.tif (which suggest that your images are two channels from one acquisition), your images are in fact identical, both with 2 channels (one for the nuclear stain, one for the lectin).

Then, click Image → Lookup Tables → Green (to change the color of the first channel to green). Move the channel slider below your image (labeled “C”) to the right (to select the second channel) and click Image → Lookup Tables → Blue (to change the color of the second channel to blue). After adjusting brightness/contrast, you should end up with something similar as the following (and similar compared to your screenshot from the paper):


Thank you very much for this.

This explains a lot.

Since they are identical, I do not need to perform an overlay.

I shall try out your solution and let you know. Once again thank you very much!

After that, I will watch videos and read up on how to perform a workflow to get the number of cells, intensity, shapes, total area, mean, circularity, solidity, and use them do statistical analysis.

Thank you so much! Have a nice day and stay safe.

1 Like

The good news is that I have achieved the desired image.

Now I need to analyse it. I am trying to {Anaylze…} but I need to set a threshold. How would one do this Uploading: 25 November 2019_STL KO1_ch00 applied the recommended colours.tif…

But I don’t know how to overcome this.

For the past week I haved watched the amazing series

Or should I use the blue image only and do apply a threshold from there, and then do analyse particles…

I need to count the total cells and then identify rounded cells vs spindle-shaped ones. Do I train the programme?

This what I have done using your amazing suggestion:

run(“Bio-Formats Importer”, “open=[C:/Users/aminu/Desktop/dataforproject/25 November 2019_STL KO1_ch00.tif] color_mode=Composite display_metadata rois_import=[ROI manager] view=Hyperstack stack_order=XYCZT”);
run(“Enhance Contrast”, “saturated=0.35”);

Apologies for the inconvenience