Posted by
Jolien Connor on
URL: http://imagej.273.s1.nabble.com/Segmentation-of-granular-stuff-tp3698915.html
Hi,
I am trying to do something similar to what many try
to do with thresholding -- find a way for the software
to pick out my pixels of interest away from the
background. In my case, it is granular "stuff" that
are intracellular inclusions in the brain. We have
many image montages taken of mouse brain sections and
we are trying to quantitate the percentage of specific
brain regions occupied by the inclusions (percent
volume). Some of the monochrome images are here:
www.waisman.wisc.edu/cmn/mutant high load.tif
www.waisman.wisc.edu/cmn/mutant high load and
faint.tif
www.waisman.wisc.edu/cmn/mutant low load and faint.tif
www.waisman.wisc.edu/cmn/control.tif
They are very large since they are montages; contact
me at
[hidden email] if you want them and
can't get them.
If you look at the pictures of the mutants compared
with the control, you can see what they are -- the
bright granular stuff all over the place. Cells that
contain the inclusions sometimes have processes that
show up, and we only want to pick out the brightest,
most granular stuff, which are the inclusions. We
want a method that can tell the difference between
mutants and controls, as well as between high load
mutants and low load mutants (lots of them versus just
a few).
The biggest problem right now seems to be that some of
our pictures are faint, possibly because the stain
weakened, our mercury bulb Atto Arc controller is
dying, or some other reason. As humans, we can still
pick them out, but we don't have a thresholding
algorithm that can handle this problems.
We have been using the Subtract Background function,
then thresholding the image, and can't get consistent
results. We use a brightfield image that lines up
with each monochrome image to trace our regions, then
have ImageJ calculate the % Area occupied by pixels
above threshold. There's no threshold we could pick
that would correctly differentiate between controls,
low load mutants and high load mutants. Any ideas?
Thanks,
Jolien Connor
University of Wisconsin