Posted by
lechristophe on
Jan 03, 2016; 4:39pm
URL: http://imagej.273.s1.nabble.com/plugin-for-crowded-field-photometry-fitting-overlapping-identical-objects-tp5015311p5015312.html
Hi Michael,
I don't know about astronomy, but in single molecule localization
microscopy (PALM/STORM) there are a few algorithms that are available for
high density data.
- ThunderSTORM is an ImageJ plugin that has a "high density" mode:
https://github.com/zitmen/thunderstorm- DAOSTORM is actually adapted from an astronomy crowded field algorithm I
think. It's Python and can be downloaded here:
https://seamusholden.wordpress.com/tag/daostorm/- There is a 3D version of DAOSTORM here (also Python):
https://github.com/ZhuangLab/storm-analysis/tree/master/3d_daostormHope this helps, and happy new year to everyone on the list!
Christophe
--
Christophe Leterrier
Researcher
Axonal Domains Architecture Team
CRN2M CNRS UMR 7286
Aix Marseille University, France
On Sun, Jan 3, 2016 at 5:12 PM, Michael Schmid <
[hidden email]>
wrote:
> Hi everyone,
>
> is there some out there who knows about an ImageJ plugin that does roughly
> what astronomers call "crowded-field photometry"?
>
> I.e., imagine that you have stars that appear slightly blurred, and the
> images of the individual stars are overlapping. Apart form different
> brightness, the stars are identical (identical point spread function PSF).
> In super-resolution microscopy one might encounter the same problem if
> there is an overlap of the image of neighboring fluorescent particles.
>
> Such images cloud be analyzed by deconvolution, but this has some
> limitations. I am looking for a plugin that tries to fit the image with
> the sum of a large number of PSF functions (preferably with subpixel
> positions). Probably 2D Gaussians would be sufficient.
>
> If someone is aware of an easy-to-understand algorithm or code that could
> be converted into an ImageJ plugin, such hints would be also helpful.
> [For the astronomers among you: yes, I am aware that there is quite some
> literature on crowded-field photometry, but delving into it and converting
> one of these methods into code is beyond what I could do within reasonable
> time.]
>
>
> Thank you,
>
> Michael
>
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