http://imagej.273.s1.nabble.com/help-with-3D-segmentation-tp5014798p5014854.html
you are working this out publicly. Regarding the coarser Z resolution,
>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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