Posted by
Jeremy Adler on
May 07, 2015; 9:00am
URL: http://imagej.273.s1.nabble.com/image-analysis-help-diffusion-tp5012746p5012753.html
The histogram of the distance transform is your answer
But for vascularity you might also consider
How making the measurement in 3D would affect the answer - a 2D measurement will overestimate distances as there may be a closer foreground pixel in a adjacent Z image. A 3D distance transform is available in ImageJ
Another complication is edge effects - the nearest pixel may be outside the image or image stack, so you need to make the distance histogram from a subregion of the image - exclude areas closer to the edge than the furthest 'true' distance you find.
-----Original Message-----
From: ImageJ Interest Group [mailto:
[hidden email]] On Behalf Of Robert Dougherty
Sent: den 7 maj 2015 02:03
To:
[hidden email]
Subject: Re: image analysis help (diffusion)
Adam,
Why isn't this just the histogram of the Euclidean distance map?
run("Dot Blot (7K)");
setOption("BlackBackground", false);
run("Make Binary");
run("Duplicate...", "title=Dot_Blot-1.jpg"); run("Distance Map"); run("Histogram");
Bob
On May 6, 2015, at 3:18 PM, Adam Huttenlocker wrote:
> Dear all,
>
> A few weeks ago I sent out a request and have yet to find a solution,
> although I'm sure a simple one exists. I am interested in whether
> there is a script that can randomly pick out 1000 black pixels in a
> black & white thresholded image and calculate the distance of each to
> its closest white pixel, and then output a frequency diagram showing
> the distribution of distances between black and white points. This is
> something useful from a biomedical viewpoint for looking at tissue vascularity and Krogh diffusion.
>
> Surely something like this must exist? Or it could be made easily? It
> seems like all one would need is a bitmap image and the coordinates
> for the black & white pixels in the image.
>
> Thanks in advance,
>
> -Adam Huttenlocker
>
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Bellevue, WA 98005
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