Posted by
Aryeh Weiss on
Nov 08, 2015; 7:10am
URL: http://imagej.273.s1.nabble.com/help-with-3D-segmentation-tp5014798p5014892.html
Further on my adventures using the DoG function:
I mentioned that the DoGPeaks function appears to find minima as well as
maxima. I decided to go to the Difference of Gaussian function
http://javadoc.imagej.net/Fiji/mpicbg/imglib/algorithm/scalespace/DifferenceOfGaussian.html#DifferenceOfGaussian(mpicbg.imglib.image.Image,%20mpicbg.imglib.image.ImageFactory,%20mpicbg.imglib.function.Converter,%20mpicbg.imglib.outofbounds.OutOfBoundsStrategyFactory,%20double[],%20double[],%20B,%20B)
Here I see that it explicitly states that it extracts local minima and
maxima of a certain size. I wonder if I can get only the maxima fro this
function.
Among its parameters are Converter, OutOfBoundsStrategy (among others).
I did not understand how to use these classes, so I wonder if someone on
this list can tell me how to use them, or even better, point me at the
documentation that might help (the class definitions in javadoc were not
enough for me).
Thank in advance.
--aryeh
On 05/11/2015 12:58 PM, Aryeh Weiss wrote:
> This is an update on the problem I posted.
>
> First, thanks to the people who replies with suggestions. From these, I
> am now following up on two of them.
>
> 1. Albert Cardona suggested trying the 3D (actually multi-D) difference
> of Gaussians (DoG) filter. This looks promising, plus it introduced me
> to imglib. It works great on isolated cells (actually, everything works
> great on isolated cells) and seems reasonable for my image, but still
> needs work. because I have such a dense collection of nuclei, it
> sometimes detects dark blobs, which are actually an approximately
> cell-sized island within a sea of nuclei.
> Albert's sample code displays the result in 3D using the 3D viewer.
> Unfortunately, java3D does not work in java 1.8, and in Java 1.6, while
> the java3D test works, the code that generates the 3D view fails -- that
> will go into a separate thread.
> The net result is that I can mark the centers of the nuclei (which is
> why it look promising) but I cannot visualize it in 3D to see if it
> really looks right.
>
> 2. Thomas Boudier suggest some 3D bandpass filtering followed by a
> seeded watershed. I will work more on finding the right parameters for
> this approach after I finish with the DoG approach. One problem is
> that the resolution in Z is much lower that in X-Y. As a result, the
> watershed does not separate the nuclei along Z. It is not clear to me
> why the DoG does. However, I still need to learn to to use the output
> of the watershed -- I may not be interpreting the output correctly.
>
> I recently got access to Imaris (basic) with a spot detector. It does a
> decent job, but since I don't have it on my computer, I plan to solve
> this with ImageJ.
>
> When I have something that works and that I can visualize, I will post
> it for the benefit of other who, like me, have to muddle their way from
> 2D to 3D.
>
> --aryeh
--
Aryeh Weiss
Faculty of Engineering
Bar Ilan University
Ramat Gan 52900 Israel
Ph: 972-3-5317638
FAX: 972-3-7384051
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