Jason Wong

Thanks everyone for the helpful replies. However I'm still a little
befuddled and confused as to what to do... I've switched to trying to
learn ImageJ, a java based image analysis program which is the PC
version of NIH Image (produced by the National Institute of Health).
But I think I'm back to where I started, basically I don't think I can
convert my mean values to density without some kind of calibration
step tablet or something like that. Here's a copy of the message I
just wrote to two other forums for help with ImageJ. Hopefully this
will clear up what I wanted to do and maybe someone can tell me how to
do it (easily preferrably!) in either photoshop or ImageJ. Thanks!

----

Hello, I'm trying to analyze hippocampal brain slices which I have
been immunostained for a neuronal marker (SNAP-25). All areas of the
slice in which synaptic connections are occurring are stained brown,
so the only unstained areas are where no tissue exists or where cell
bodies are located. The hippocampus is composed of several regions of
different neuron types (e.g. CA1, CA3, dentate gyrus), which are
clearly demarked using this stain by differential staining
intensities. However due to difficulties with the staining protocol,
staining intensities were not uniform from day to day, brain to brain,
and even parallel slice to slice. So to normalize this, I'm going to
be dealing with ratios between one hippocampal region and another.

So far I've converted my RGB images to 8-bit grayscale by selecting
Image -> Type -> 8-bit. I then openned up an image of a scale bar
used to set the scale by selecting Analyze -> Set Scale. Next I drew
a rectangle area selection tool to draw a square of fixed area (88
squared pixels). I then moved the square to the CA1 region, and
recorded the mean gray value by selecting Analyze -> Measure. Finally
I moved the selection square to record the mean gray value for a total
of 3 regions per image.

What I'm mostly confused with is what the mean gray value actually
MEANS. For the darker regions, I get a lower mean value but for the
lighter regions, I get a greater one. That seems to go against what I
would think of intuitively of what I actually want -- which is pixel
density. So if region A is darker than region C, I'd get a larger
value for region A. Final analysis would involve taking the ration of
A to C and comparing it with another region, such as B to C.

Someone mentioned something about calibrating my images. I'm not too
sure what this means or entails, but I don't think I have access to a
calibrated optical density step tablet. I don't know if that would
help either because each image I took might have slight changes in
brightness as I often fiddled around with the imaging system to
produce the best "looking" picture. But I figure the ratios idea will
help solve that dilema.

If anyone can understand what I'm trying to do and give me some help,
please please please do! Thank you