particle tracking

[Kuljis, Dika Ana]

I am using ImageJ to measure areas of axons and their surrounding myelin
sheathes. ImageJ reports each "particle" area which is in my situation either
the axon or the myelin and are similar to a donut and a donut-hole shape. I need
to be able to attribute each donut-hole (the axon) to its surrounding donut
(myelin), but do not know if there is any way to label, track, or verify the
pairing.
 
I am working with two images of one picture: one that shows only the donut
shaped myelin, and one that shows the donut-hole shaped center axon. As was
explained to me, area assessment is ordinal from the top left of the image and
goes downward. However, the location of my particles isn't always so clear cut.
For instance, the myelin may be higher in one pass then it would be for its
respective axon and therefore, might be attributed to an axon not its own. These
are irregular shapes and sometimes thicker or thinner, and so the order will be
flip flopped and the order of my axon image will not correspond to the order of
my myelin image.
 
Is there some feature available that will help me track which particle is being
assigned which number? Are there any suggestions as tho how I can use ImageJ to
get around this problem?
 
 





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[karo03]

I have the same problem. The attached macro might help. Possibly it  
has to be adapted to the already prepared myelin and axon images. The  
idea to join or relate the axon to the surrounding myelin is using  
the feature 'integrated density' on the axon image, where each pixel  
is set to 1. intden gives than the axon area in pixels. Caution if  
scaling is used, because this feature is not scaled!

The macro fails, if nerv fibres build a structure with non-axon  
interior. Axon area is the interior of each connected myelin  
particle. There is a outcommented part for waiting for user  
interaction. This would need a plugin package I got from Volker  
Bäcker from Montpellier.

let me hear if it helps and share improvements.

Regards
Karsten

Am 24.07.2007 um 20:47 schrieb Kuljis, Dika Ana:

> I am using ImageJ to measure areas of axons and their surrounding  
> myelin
> sheathes. ImageJ reports each "particle" area which is in my  
> situation either
> the axon or the myelin and are similar to a donut and a donut-hole  
> shape. I need
> to be able to attribute each donut-hole (the axon) to its  
> surrounding donut
> (myelin), but do not know if there is any way to label, track, or  
> verify the
> pairing.
>
> I am working with two images of one picture: one that shows only  
> the donut
> shaped myelin, and one that shows the donut-hole shaped center  
> axon. As was
> explained to me, area assessment is ordinal from the top left of  
> the image and
> goes downward. However, the location of my particles isn't always  
> so clear cut.
> For instance, the myelin may be higher in one pass then it would be  
> for its
> respective axon and therefore, might be attributed to an axon not  
> its own. These
> are irregular shapes and sometimes thicker or thinner, and so the  
> order will be
> flip flopped and the order of my axon image will not correspond to  
> the order of
> my myelin image.
>
> Is there some feature available that will help me track which  
> particle is being
> assigned which number? Are there any suggestions as tho how I can  
> use ImageJ to
> get around this problem?
>
>
>
>
>
>
>
> The information transmitted in this electronic communication is  
> intended only for the person or entity to whom it is addressed and  
> may contain confidential and/or privileged material. Any review,  
> retransmission, dissemination or other use of or taking of any  
> action in reliance upon this information by persons or entities  
> other than the intended recipient is prohibited. If you received  
> this information in error, please contact the Compliance HelpLine  
> at 800-856-1983 and properly dispose of this information.

[Michael Cammer]

We had the exact same problem with measuring dark myelin around light
axons.  The way we dealt with it was to segment out the myelin
rings.  Then, for each extracted region of interest  duplicate the
image, clear outside the myelin and then do the measurements within
the region of interest.   We stored the results in our own arrays and
printed them out in a tabbed table at the end. This solved the
problems of centroids of myelin that did not fall neatly within the
axons and guaranteed a one-to-one relationship in the measurements.

____________________________________________________________________________
Michael Cammer   Analytical Imaging Facility   Albert Einstein Coll. of Med.
URL:  http://www.aecom.yu.edu/aif/