Please help with standardized threshold method for image series

[verant]

Hi,
 I have 8-bit greyscale images of bat wings that I am trying to use thresholds to measure an aggregate of particles within the ROI (the wing) and have been getting inconsistent results with various threshold methods (autothreshold options) from image to image. All the images were captured with the same camera settings and the channels were split using Photoshop. These images represent just the red channel. I have also tried just using Process-> Make Binary to transform the images but this has been inconsistent also between images that appear similar.
 Any tips or suggestions for this task would be very appreciated! I am new at this and have hit a road block I can't find my way around or through.

Thanks!

Michelle

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[Kenton Arkill]

Hi
Somebody else will have a better help with he segmentation part but unless you are interested in the intensity (not just number of points) segmentation is easier if you have floated all the images around a common mean and standard deviation, and done a bandpass filter to suppress noise.
Kenton

Kenton Arkill
GB U23 Ladies'
Underwater Hockey Coach
GB Masters
Underwater Hockey Manager




On 2 Jul 2012, at 22:13, Michelle Verant wrote:

> Hi,
>  I have 8-bit greyscale images of bat wings that I am trying to use thresholds to measure an aggregate of particles within the ROI (the wing) and have been getting inconsistent results with various threshold methods (autothreshold options) from image to image. All the images were captured with the same camera settings and the channels were split using Photoshop. These images represent just the red channel. I have also tried just using Process-> Make Binary to transform the images but this has been inconsistent also between images that appear similar.
>  Any tips or suggestions for this task would be very appreciated! I am new at this and have hit a road block I can't find my way around or through.
>
> Thanks!
>
> Michelle
>
> --
> ImageJ mailing list: http://imagej.nih.gov/ij/list.html

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[verant]

Hi Kenton,

 That is helpful advice, I am just interested in point counts (not intensity).  I am not sure what you mean by floating images around a mean and st dev and using a bandpass filter but I will look into it.

 Does ImageJ have this capability or is this something I need to do (ie in Photoshop or other) before importing the image into ImageJ?

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[Kenton Arkill]

Hi
a bandpass filter is in the 'process>FFT' menu.
Floating means that each image has the same mean pixel value and the same
standard deviation. I find it really useful as it means the same threshold
can often be used on all the images. Here is my macro, it floats the stack
to the values of the first slice (so make sure it is a good image):

run("32-bit");

setSlice(1);

getRawStatistics(nPixels, meanref, min, max, stdref, histogram);


for (i = 1; i <= nSlices; i++) {

       setSlice(i);

       getRawStatistics(nPixels, meani, min, max, stdi, histogram);

       run("Subtract...", "value="+meani+" slice");

       run("Divide...", "value="+stdi+" slice");

       run("Multiply...", "value="+stdref+" slice");

       run("Add...", "value="+stdref+" slice");

}

run("Enhance Contrast", "saturated=0.35");

setSlice(1);


Regards

Kenton

On 3 July 2012 17:49, Michelle Verant <[hidden email]> wrote:

> Hi Kenton,
>
>  That is helpful advice, I am just interested in point counts (not
> intensity).  I am not sure what you mean by floating images around a mean
> and st dev and using a bandpass filter but I will look into it.
>
>  Does ImageJ have this capability or is this something I need to do (ie in
> Photoshop or other) before importing the image into ImageJ?
>
> --
> ImageJ mailing list: http://imagej.nih.gov/ij/list.html
>

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ImageJ mailing list: http://imagej.nih.gov/ij/list.html

[verant]

Thanks for the explanation. That could be very useful! I'll try it out

michelle

On 07/03/12, Kenton Arkill  wrote:

> Hi
> a bandpass filter is in the 'process>FFT' menu.
> Floating means that each image has the same mean pixel value and the same
> standard deviation. I find it really useful as it means the same threshold
> can often be used on all the images. Here is my macro, it floats the stack
> to the values of the first slice (so make sure it is a good image):
>
> run("32-bit");
>
> setSlice(1);
>
> getRawStatistics(nPixels, meanref, min, max, stdref, histogram);
>
>
> for (i = 1; i <= nSlices; i++) {
>
> setSlice(i);
>
> getRawStatistics(nPixels, meani, min, max, stdi, histogram);
>
> run("Subtract...", "value="+meani+" slice");
>
> run("Divide...", "value="+stdi+" slice");
>
> run("Multiply...", "value="+stdref+" slice");
>
> run("Add...", "value="+stdref+" slice");
>
> }
>
> run("Enhance Contrast", "saturated=0.35");
>
> setSlice(1);
>
>
> Regards
>
> Kenton
>
> On 3 July 2012 17:49, Michelle Verant <[hidden email]> wrote:
>
> > Hi Kenton,
> >
> > That is helpful advice, I am just interested in point counts (not
> > intensity). I am not sure what you mean by floating images around a mean
> > and st dev and using a bandpass filter but I will look into it.
> >
> > Does ImageJ have this capability or is this something I need to do (ie in
> > Photoshop or other) before importing the image into ImageJ?
> >
> > --
> > ImageJ mailing list: http://imagej.nih.gov/ij/list.html
> >
>
> --
> ImageJ mailing list: http://imagej.nih.gov/ij/list.html

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