Posted by
Olivier Burri on
Jan 14, 2014; 8:50am
URL: http://imagej.273.s1.nabble.com/BrdU-cell-counting-tp5006086p5006114.html
Hello,
The simplest and usually still rather accurate way of doing this is to go for a threshold and measure the area covered by the cells.
Choosing the threshold: Try and use all the automatic methods imageJ has to offer and see if one of them matches a threshold that, in your expert opinion, captures the true BrdU area. Be careful using a manual threshold for each image, you might introduce bias. Maybe jumble your image names and offer a colleague a piece of cake for selecting the thresholds for you blindly.
You can then divide the area by the average size of a single BrdU positive cell. Measure a bunch of these individual cells to get a good statistic, get its standard deviation so that you can then get an estimate of the error you're making.
Eg:
Area: 5300 um2
Single cell mean: ~35um (measured over 100+ cells)
Single cell SD: 5.32um
Relative SD = 5.32/35 = 15.2%
Estimation on the number of cells: 5300/35 = 151.43 cells
Standard deviation : 151.43*0.152 = 23 cells
This usually gives you a good idea whether you can actually measure a difference between conditions. Once you have these data, you can use power-law calculations to see how many samples you'll need, for example.
http://biostat.mc.vanderbilt.edu/wiki/Main/PowerSampleSizeAll the best,
Oli
Olivier Burri
Engineer - Image Processing
& Software Development
EPFL - SV - PTECH - PTBIOP
-----Original Message-----
From: ImageJ Interest Group [mailto:
[hidden email]] On Behalf Of Josue
Sent: vendredi 10 janvier 2014 21:27
To:
[hidden email]
Subject: BrdU cell counting
Hello experts.I would like to know what method do you recommend for cell counting to measure cell proliferation in the SVZ when there are some clusters of uncountable cells?
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