Here is a very simple guide for determining the level of fluorescence in a given region (e.g nucleus)

1.Select the cell of interest using any of the drawing/selection tools (i.e. rectangle, circle, polygon or freeform)

2.From the Analyze menu select “set measurements”. Make sure you have AREA, INTEGRATED DENSITY and MEAN GRAY VALUE selected (the rest can be ignored).

3.Now select “Measure” from the analyze menu or hit cmd+m (apple). You should now see a popup box with a stack of values for that first cell.

4.Now go and select a region next to your cell that has no fluroence, this will be your background.

NB: the size is not important. If you want to be super accurate here take 3+ selections from around the cell.

5.Repeat this step for the other cells in the field of view that you want to measure.

6.Once you have finished, select all the data in the Results window, and copy (cmd+c) and paste (cmd+v) into a new excel worksheet (or similar program)

7.Use this formula to calculate the corrected total cell fluorescence (CTCF).

NB: You can use excel to perform this calculation for you.CTCF = Integrated Density – (Area of selected cell X Mean fluorescence of background readings)

8.Make a graph and your done. Notice that in this example that the rounded up mitotic cell appears to have a much higher level of staining, but this is actually due to its smaller size, which concentrates the staining in a smaller space. So if you just used the raw integrated density you would have data suggesting that the flattened cell has less staining then the rounded up one, when in reality they have a similar level of fluorescence.

I hope this will help,

with kind regards

The above is used in the image J software

I've used Image J for this purpose and measured nuclei intensity of many cells over time, keeping track of each cell separately (in a grayscale movie). To do this I open my file, then go to Analyze tab and choose "set measurement". Here you choose what you want to measure (area, st dev., min/max gray value for example). Then under Analyze tab I choose "tools" and "ROI manager". I then choose the shape I wish to use from the main bar (oval for nuclei). ROI to be measured for each cell is then selected and followed by typing "t" or pushing "add" buttin for each selection. Selecting "show all" and "labels" in hte ROI manager box will help you keep track. Then still in the ROI manager I select "more' and "multi'measure". At this point you will be gien a choice on how to best lay-out your data. Once you have it as you wish, then just move it to excel for further analysis.

Thresholded images are not binary unless you click Apply. Analyze Particles applied to a thresholded image will give you intensity values, as selected in Set Measurements where you also click on the strict to threshold button.

Hi Mikael,

As people above have said imagej (or for me i use the Fiji distribution www.fiji.sc) is easy enough to do it. But instead of playing around with ROIs its easier to just redirect your binary image to measure the the original image. You can download some notes i have created (part of a much larger course) from here

https://dl.dropboxusercontent.com/u/11163658/Technical%20Note%2008%20-%20Cell%20Counting.pdf

https://dl.dropboxusercontent.com/u/11163658/Technical%20Note%2009%20-%20Cell%20Segmentation.pdf

The demo images the notes reference can be downloaded form here https://dl.dropboxusercontent.com/u/11163658/Segmentation.zip

They will take you through cell segmentation and measuring intensities etc using he created binary masks.

If you are doing a lot of this it can also be scripted to make it all automatic for you.

let me know if you need anything more

Cheers

cam

If the cells are dispersed, i.e. not overlapping, I would recommend that you use MATLAB. It is quite straightforward to isolate the cellular objects, and to relate them to a particular part of the original image. As you have realized through your studies this involves a conversion to binary format - but you can use the binary object locations to cut out the relevant objects of the original image, and thus being able to measure intensity.

If you send me a sample image with disperse cells, I can have a look and see how easy/difficult it would be to extract intensities for each cell automatically.

You can download an example pipeline that works in the free CellProfiler software to measure intensity per cell very easily and automatically (you can measure total intensity, mean intensity, max intensity, etc). Check out the Human or Fly example pipelines here:

http://cellprofiler.org/examples.shtml

Thanks everyone! I found that in ImageJ, the redirection method is indeed extremely simple. I posted a simple script I made for that purpose but it seems to have disappeared from here, so maybe I try again.... This is for measuring areas and average intensities in nuclei defined by DAPI signal in one image in two other images. This is just very very simple, so DAPI thresholds, particle sizes for detection etc obviously need to be adjusted per each case.

Very good point Julia - unless you have only thousands of cells to analyze :)

Hello, Julia P Hunn ,

Do you have any protocol to measure fluorescent signal intensity in FACS? 

This is really helpful, thank you. 

To anyone stumbling across this post from the past the links i included are no longer current.

The following links are to the complete manual the tech notes are from and the demo images for it all

Manual

https://cloudstor.aarnet.edu.au/plus/index.php/s/6CENpiAC8Y42HWU

Demo images

https://cloudstor.aarnet.edu.au/plus/index.php/s/9be59b14867b17aa7f1e351c66681bd5

Dear Cameron,

Unfortunately, the files are not found on the server anymore. Can you upload them again?

Many thanks!

Dear Cameron, I am also looking for these documents (stumbled across the post just now). Do you have the a manual still available?

Regards

Lize

hello I’m looking for it too thank u to share the manual

regards