Re: [EXTERNAL] Help with quantifying pictures after channel splitting

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Re: [EXTERNAL] Help with quantifying pictures after channel splitting

Citron, Bruce
Stephanie-
This seems like one of the more common ImageJ tasks for microscopy, but more info is needed.  Also, if red is the color of interest, why use the blue channel?

Exactly what kind of number are you trying to obtain- number of red particles?  average intensity of any red staining?  average intensity of all red particles?  Are there lots of images to examine indicating that you'd want to execute some batch processing?

There are also several automatic thresholding routines available in ImageJ and one of these might work better than Default (see what is available under that drop down).
-Bruce

-----Original Message-----
From: Stephanie Klett <[hidden email]<mailto:[hidden email]>>
Reply-To: ImageJ Interest Group <[hidden email]<mailto:[hidden email]>>
Date: Wednesday, February 4, 2015 9:44 AM
To: ImageJ Interest Group <[hidden email]<mailto:[hidden email]>>
Subject: [EXTERNAL] Help with quantifying pictures after channel splitting

Dear Image J discussion group,
I have a question about how I can quantify my digital microscopic images
(.jpg) In my case I done a immunological staining where red is the colour of
interest. Therefore, I split the channels and use the blue labelled picture
and apply the function Threshold... (under Image-->Adjust-->). Then I get a
histogram and an automatically adjustment of the colour sensibility (?). My
question is what should I keep in mind when I want to compare several
images. Do I have to adjust always the same sensibility (from the rage of 0
to 255) or do I choose the automatically adjustment? My problem is, that
sometimes the automatically adjustment represent the quantification better
than the sensibility rate that I decided to use and other way around. Which
way is more unbiased or do I have to do a completely other procedure?

Here I display screen shots where I document my way and may problem more
exemplified.

Fig. 1 Opened a file and split the channels

Fig. 2 Apply the function ³Threshold...² on the image labelled "blue³
Fig. 3 Display the automatically adjustment of 228

Fig. 4 Corrected the threshold to 180

Fig. 5 A new image, display the automatically threshold of 222

Fig. 6 Corrected the threshold to the undoing rate of 180


I¹m very happy if you can help me and looking forward to your answer.

Thank you for your attention

Best regards
Stephanie

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