Posted by
Aryeh Weiss on
Nov 05, 2015; 10:58am
URL: http://imagej.273.s1.nabble.com/help-with-3D-segmentation-tp5014798p5014851.html
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
On 01/11/2015 4:22 PM, Albert Cardona wrote:
>
> Try this:
>
>
https://www.ini.uzh.ch/~acardona/fiji-tutorial/#find-peaks>
> Works with difference of gaussian to find peaks, in nd (the example is
> in 3D just like in your data).
>
> The key in DoG is to determine the two sigmas. A bit of experimentation
> will take you there.
>
> Albert
>
>
> On Nov 1, 2015, at 8:06 AM, Aryeh Weiss <
[hidden email]
> <mailto:
[hidden email]>> wrote:
>
>> I have been asked to do a 3D segmentation of a DAPI stained image,
>> such as the image stack available at:
>>
https://drive.google.com/open?id=0B9hvIdSL8kGyY0NiRzRkaXlINmM>>
>> I find that I can do very well in 2D by blurring the image and doing
>> peak detection, or gray-scale watershed.
>> Gabriel Landini's domes followed by a peak detection or thresholding
>> step also works nicely.
>> However, I have not succeeded in extending this to 3D, using the 3D
>> morphological segmentation tools.
>>
>> A 3D-domes would be nice, but I have not found that.
>> I tried peak detection or 2D-domes and then 3D object counting, but
>> there is still too much overlap in the Z-direction, so that nuclei which
>> overlap vertically are counted as one object.
>>
>> So I seek to tap into the knowledge available on this list, because I
>> am sure someone has already done this type of segmentation.
>>
>> Thanks in advance
>> --aryeh
>>
>> --
>> Aryeh Weiss
>> Faculty of Engineering
>> Bar Ilan University
>> Ramat Gan 52900 Israel
>>
>> Ph: 972-3-5317638
>> FAX: 972-3-7384051
>>
>>
>> --
>> ImageJ mailing list:
http://imagej.nih.gov/ij/list.html--
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