Using ImageJ to recognise synapses - very grateful for any help

[ajeans]

Hello all,

Can anyone help a relatively inexperienced user with suggestions on how to
do the following with plugins or *very* simple macros:

I am a neuroscientist and have been trying to identify synapses in images
of nerve cells which have been labelled up with two different coloured
markers. Essentially, both of the markers exist as variously-sized puncta
scattered across the whole image, and in various places different coloured
puncta will overlap. I want to identify and analyse only those puncta from
one channel (red as it stands) which have any overlap at all with any of
the puncta from the other (green) channel. If a red punctum has overlap
with a green one, I want to select that whole red punctum, not just the
overlapping part, for analysis. The analysis of selected puncta is just
simple diameter and average fluorescence measurement.

I have got as far as thresholding the raw images and using the particle
analyzer to define the puncta themselves. How to identify that subset which
has overlap with another channel is the bit I am stuck on.

I've tried lots of Google searches which give lots of variations of
colocalisation analysis, but that's not really what I'm looking for. I just
want to use the presence or absence of colocalisation as a binary filter to
sort red channel puncta for analysis or not.

Does anybody have any thoughts, or know of a plugin or macro that could do
something like this? Any help very gratefully accepted!

Thanks very much,

Alex Jeans

Oxford, UK

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[Straub, Volko A. (Dr.)]

Hi Alex,

If you have already thresholded your images, you can just simply combine the two thresholded images with an "AND" operator (Process>Image Calculator). You can then use the resulting image as the seed for a binary reconstruction using Gabriel Landini collection of morphological operators for ImageJ (http://www.dentistry.bham.ac.uk/landinig/software/software.html).  Following the reconstruction that should restore the original size of the particles based on the image that you selected as the Mask image which contain an overlapping region. You can then use the Particle Analyser for your measurements.

I hope this helps,
Volko


-----Original Message-----
From: ImageJ Interest Group [mailto:[hidden email]] On Behalf Of Alex Jeans
Sent: 04 September 2013 16:03
To: [hidden email]
Subject: Using ImageJ to recognise synapses - very grateful for any help

Hello all,

Can anyone help a relatively inexperienced user with suggestions on how to do the following with plugins or *very* simple macros:

I am a neuroscientist and have been trying to identify synapses in images of nerve cells which have been labelled up with two different coloured markers. Essentially, both of the markers exist as variously-sized puncta scattered across the whole image, and in various places different coloured puncta will overlap. I want to identify and analyse only those puncta from one channel (red as it stands) which have any overlap at all with any of the puncta from the other (green) channel. If a red punctum has overlap with a green one, I want to select that whole red punctum, not just the overlapping part, for analysis. The analysis of selected puncta is just simple diameter and average fluorescence measurement.

I have got as far as thresholding the raw images and using the particle analyzer to define the puncta themselves. How to identify that subset which has overlap with another channel is the bit I am stuck on.

I've tried lots of Google searches which give lots of variations of colocalisation analysis, but that's not really what I'm looking for. I just want to use the presence or absence of colocalisation as a binary filter to sort red channel puncta for analysis or not.

Does anybody have any thoughts, or know of a plugin or macro that could do something like this? Any help very gratefully accepted!

Thanks very much,

Alex Jeans

Oxford, UK

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[Gabriel Landini]

On Wednesday 04 Sep 2013 16:03:01 Alex Jeans wrote:
> I have got as far as thresholding the raw images and using the particle
> analyzer to define the puncta themselves. How to identify that subset which
> has overlap with another channel is the bit I am stuck on.

We have implemented a spatial reasoning logic model that could be used to find
this kind of relationships between binary objects across images (or channels
in a stack).

http://www.dentistry.bham.ac.uk/landinig/software/spatial/rcc8d.html

The IEEE PAMI paper listed in that page gives all the theoretical work.

Ask if you have any questions on this.

Cheers

Gabriel

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[Gabriel Landini]

On Wednesday 04 Sep 2013 16:53:37 you wrote:
> If you have already thresholded your images, you can just simply combine the
> two thresholded images with an "AND" operator (Process>Image Calculator).
> You can then use the resulting image as the seed for a binary
> reconstruction using Gabriel Landini collection of morphological operators
> for ImageJ
> (http://www.dentistry.bham.ac.uk/landinig/software/software.html).
> Following the reconstruction that should restore the original size of the
> particles based on the image that you selected as the Mask image which
> contain an overlapping region.

That would miss regions that do not really overlap on the lattice, but
"should" overlap in the real world, like 45 degree (diagonal) lines that cross
at a 90 degree angle exactly at a corner (i.e. they do not share a pixels).
That is the PO* relation and shown in the link I posted earlier.  The AND of
those 2 lines returns an empty result. The RCC8D plugin can detect those
relations. Connectedness in square grids has some non-intuitive properties.

Cheers

Gabriel

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[Stoyan Pavlov]

Wow! That is amazing plugin, prof. Landini! Thank you very much for
creating it and for the nice tutorial!

Stoyan Pavlov


2013/9/4 Gabriel Landini <[hidden email]>

> On Wednesday 04 Sep 2013 16:53:37 you wrote:
> > If you have already thresholded your images, you can just simply combine
> the
> > two thresholded images with an "AND" operator (Process>Image Calculator).
> > You can then use the resulting image as the seed for a binary
> > reconstruction using Gabriel Landini collection of morphological
> operators
> > for ImageJ
> > (http://www.dentistry.bham.ac.uk/landinig/software/software.html).
> > Following the reconstruction that should restore the original size of the
> > particles based on the image that you selected as the Mask image which
> > contain an overlapping region.
>
> That would miss regions that do not really overlap on the lattice, but
> "should" overlap in the real world, like 45 degree (diagonal) lines that
> cross
> at a 90 degree angle exactly at a corner (i.e. they do not share a pixels).
> That is the PO* relation and shown in the link I posted earlier.  The AND
> of
> those 2 lines returns an empty result. The RCC8D plugin can detect those
> relations. Connectedness in square grids has some non-intuitive properties.
>
> Cheers
>
> Gabriel
>
> --
> ImageJ mailing list: http://imagej.nih.gov/ij/list.html
>

--
Dr. Stoyan P. Pavlov, MD, PhD
Departament of Anatomy, Histology and Embryology
Medical University "Prof. Dr. Paraskev Stoyanov", Varna
Prof. Marin Drinov Str.55
9002 Varna
 Bulgaria
Tel: +359 (0) 52 - 677 - 052
e-mail: [hidden email]

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