Macro for recognize shapes.

[Brioso Jimenez, Jose]

Hello everyone!


I am trying to use ImageJ to measure the fluorescence of a transgenic strain of C. elegans that harbours both GFP and RFP, for that I am taking multiple pictures of them in different conditions, with a lot of replicas.


Because I have SO MUCH data I need to find a way that let ImageJ recognize the shape of the worms so I can measure the fluorescence per area with ImageJ.


I am taking three pictures per measurement, one without filters, one with GFP filter and the last one with RFP filter. (Pics attached)


How can I do to develop a macro that allow ImageJ to recognize the shapes so I can measure the fluorescence, and I do not have to draw of the worm manually (that is painfull).

?
Thank you all for your time!

Best regards.

JL. Brioso?

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[G. Esteban Fernandez]

1. Image > Adjust > Threshold (to select the worms)
2. Analyze > Set Measurements and check the box for Mean Gray Value
and/or Integrated Density.
3. Analyze > Analyze Particles.

-Esteban

On Mon, Mar 2, 2015 at 2:30 AM, Brioso Jimenez, Jose
<[hidden email]> wrote:

> Hello everyone!
>
>
> I am trying to use ImageJ to measure the fluorescence of a transgenic strain of C. elegans that harbours both GFP and RFP, for that I am taking multiple pictures of them in different conditions, with a lot of replicas.
>
>
> Because I have SO MUCH data I need to find a way that let ImageJ recognize the shape of the worms so I can measure the fluorescence per area with ImageJ.
>
>
> I am taking three pictures per measurement, one without filters, one with GFP filter and the last one with RFP filter. (Pics attached)
>
>
> How can I do to develop a macro that allow ImageJ to recognize the shapes so I can measure the fluorescence, and I do not have to draw of the worm manually (that is painfull).
>
> ?
> Thank you all for your time!
>
> Best regards.
>
> JL. Brioso?
>
> --
> ImageJ mailing list: http://imagej.nih.gov/ij/list.html

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[PEARSON Matthew]

Hi all,

One of our facility users would like to put some numbers on the distribution of their nuclear protein in 2D which in some cells localises more to the periphery and in others is more randomly distributed.  Is there an easy way to quantify this?  Ideally by segmenting the entire nucleus then using some parameter to measure the intensity and distribution within.

HIstorically, here we have divided the nucleus into 5 concentric bands each with equal area and then measured the intensity within each ring as a means to be able to compare distribution between different nuclei.

Thanks for the help,

Matt






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[Romain Guiet]

Hi Matt,
without any image, it's a bit difficult to answer... but if you can get a segmented image of the nuclei and of your nuclear protein (let's assume you have spots) you could try to:
- generate a distance map of the nuclei image
and then
-measure the value of each spot (from nuclear protein) in this distance map image.
This way, you could observe that for some nuclei the nuclear protein have small distance value (close to the periphery) and for other they have more randomly distributed value...
Cheers,
Romain


---------------------------------------------------------------
Dr. Romain Guiet
Bioimaging and Optics Platform (PT-BIOP)
Ecole Polytechnique Fédérale de Lausanne (EPFL)
Faculty of Life Sciences
Station 19, AI 0140
CH-1015 Lausanne

Phone: [+4121 69] 39629
http://biop.epfl.ch/
---------------------------------------------------------------

________________________________________
De : ImageJ Interest Group [[hidden email]] de la part de PEARSON Matthew [[hidden email]]
Envoyé : lundi 2 mars 2015 16:45
À : [hidden email]
Objet : How to measure nuclear protein spatial distribution

Hi all,

One of our facility users would like to put some numbers on the distribution of their nuclear protein in 2D which in some cells localises more to the periphery and in others is more randomly distributed.  Is there an easy way to quantify this?  Ideally by segmenting the entire nucleus then using some parameter to measure the intensity and distribution within.

HIstorically, here we have divided the nucleus into 5 concentric bands each with equal area and then measured the intensity within each ring as a means to be able to compare distribution between different nuclei.

Thanks for the help,

Matt






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Scotland, with registration number SC005336.

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[Dimiter Prodanov-3]

Hello,

If your protein is sufficiently sparsely localized you can treat it as a
point process
Look for example here:
http://www.ncbi.nlm.nih.gov/pubmed/17049615
http://www.ncbi.nlm.nih.gov/pubmed/23785482


If the protein is dense you can treat it as a Gaussian random field.
I'll be happy to answer more questions.

best regards,

D Prodanov

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[PEARSON Matthew]

Hi Dimiter,

Thanks for the info.  I was asking on behalf of one of our facility users and we came up with a solution in the end using the radial profile feature of imageJ.

Thanks,

Matt


On 12 Mar 2015, at 08:21, Dimiter Prodanov <[hidden email]> wrote:

> Hello,
>
> If your protein is sufficiently sparsely localized you can treat it as a
> point process
> Look for example here:
> http://www.ncbi.nlm.nih.gov/pubmed/17049615
> http://www.ncbi.nlm.nih.gov/pubmed/23785482
>
>
> If the protein is dense you can treat it as a Gaussian random field.
> I'll be happy to answer more questions.
>
> best regards,
>
> D Prodanov
>
> --
> ImageJ mailing list: http://imagej.nih.gov/ij/list.html
>

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[ethidium76]

Hi all,

Is there a plug in available that will sort stacks by a image intensity?

Best,

MSB

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