quantify the fibers with the red color

[thuraya]

i need to quantify the dense red color in the image please help me...

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[thuraya]

i need to quantify the dense red color in the image please help me...

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[John Hayes]

Hi,

Can you tell us what you need to quantify about the dense red fibers in the image? The number of reddish pixels, the length of the fibers in the imaging field, etc.???

In any case, I recommend starting by splitting the RGB into separate channels, and thresholding the red channel to your liking to identify what you think is signal and exclude the noise... Then, « quantify » based on whatever is physiologically-relevant to your case, but it’s unclear what that is right now.

Best,

John

Le 2 juil. 2013 à 21:32, Thuraya Medhat a écrit :

> i need to quantify the dense red color in the image please help me...
>
> --
> ImageJ mailing list: http://imagej.nih.gov/ij/list.html
> <image4072-001.jpg>

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[thuraya]

i need the pixels of the reddish fibers percent to the whole image so i can
quantify how much the fibrosis is


On Tue, Jul 2, 2013 at 9:41 PM, John Hayes <[hidden email]> wrote:

> Hi,
>
> Can you tell us what you need to quantify about the dense red fibers in
> the image? The number of reddish pixels, the length of the fibers in the
> imaging field, etc.???
>
> In any case, I recommend starting by splitting the RGB into separate
> channels, and thresholding the red channel to your liking to identify what
> you think is signal and exclude the noise... Then, « quantify » based on
> whatever is physiologically-relevant to your case, but it’s unclear what
> that is right now.
>
> Best,
>
> John
>
> Le 2 juil. 2013 à 21:32, Thuraya Medhat a écrit :
>
> > i need to quantify the dense red color in the image please help me...
> >
> > --
> > ImageJ mailing list: http://imagej.nih.gov/ij/list.html
> > <image4072-001.jpg>
>
> --
> ImageJ mailing list: http://imagej.nih.gov/ij/list.html
>

... [show rest of quote]

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[pang]

[cid:image001.png@01CE773C.911CCD10]



I used the following macro to quantify the area. There is some artifact due to the edge circle,



run("Split Channels");



selectWindow("image4072-001.jpg (green)");  // I like to use green as it is darkest in red, providing best contrast.

setAutoThreshold("Default dark");

//run("Threshold...");

run("Measure");



run("Subtract Background...", "rolling=50 light");



setThreshold(155, 227);

run("Measure");



My estimation is 121097/1044914, about 11% of area (partial circle).

121097 is the pixel number for the red color, 10440914 is the pixels within the circle.





-----Original Message-----
From: ImageJ Interest Group [mailto:[hidden email]] On Behalf Of John Hayes
Sent: Tuesday, July 02, 2013 3:41 PM
To: [hidden email]
Subject: Re: quantify the fibers with the red color



Hi,



Can you tell us what you need to quantify about the dense red fibers in the image? The number of reddish pixels, the length of the fibers in the imaging field, etc.???



In any case, I recommend starting by splitting the RGB into separate channels, and thresholding the red channel to your liking to identify what you think is signal and exclude the noise... Then, « quantify » based on whatever is physiologically-relevant to your case, but it's unclear what that is right now.



Best,



John



Le 2 juil. 2013 à 21:32, Thuraya Medhat a écrit :



> i need to quantify the dense red color in the image please help me...

>

> --

> ImageJ mailing list: http://imagej.nih.gov/ij/list.html

> <image4072-001.jpg>



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[thuraya]

first of all thanks alot but i'm alittle confused
i used the green channel as you said cuase it's the best
then i did these steps but it didn't give me your result
: - image , adjust, threshold
  - set to 155 ,227
- run subtract background
it did't give me these result at all ... please help me ,,

---------- Forwarded message ----------
From: Pang, Zhengyu (GE Global Research) <[hidden email]>
Date: Tue, Jul 2, 2013 at 9:57 PM
Subject: Re: quantify the fibers with the red color
To: [hidden email]


[cid:image001.png@01CE773C.911CCD10]



I used the following macro to quantify the area. There is some artifact due
to the edge circle,



run("Split Channels");



selectWindow("image4072-001.jpg (green)");  // I like to use green as it is
darkest in red, providing best contrast.

setAutoThreshold("Default dark");

//run("Threshold...");

run("Measure");



run("Subtract Background...", "rolling=50 light");



setThreshold(155, 227);

run("Measure");



My estimation is 121097/1044914, about 11% of area (partial circle).

121097 is the pixel number for the red color, 10440914 is the pixels within
the circle.





-----Original Message-----
From: ImageJ Interest Group [mailto:[hidden email]] On Behalf Of John
Hayes
Sent: Tuesday, July 02, 2013 3:41 PM
To: [hidden email]
Subject: Re: quantify the fibers with the red color



Hi,



Can you tell us what you need to quantify about the dense red fibers in the
image? The number of reddish pixels, the length of the fibers in the
imaging field, etc.???



In any case, I recommend starting by splitting the RGB into separate
channels, and thresholding the red channel to your liking to identify what
you think is signal and exclude the noise... Then, « quantify » based on
whatever is physiologically-relevant to your case, but it's unclear what
that is right now.



Best,



John



Le 2 juil. 2013 à 21:32, Thuraya Medhat a écrit :



> i need to quantify the dense red color in the image please help me...

>

> --

> ImageJ mailing list: http://imagej.nih.gov/ij/list.html

> <image4072-001.jpg>



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[Benjamin Grant]

Running "subtract background" after threshholding will not do anything. Try
running that first, then thresholding, that might be your issue.

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[Stoyan Pavlov]

Hi Thuraya

In brightfield images one SHOULD NOT quantify brightness but density,
because the image is formed via absorbtion of certain quantity of light of
certain wavelength.It is a very common  mistake to treat brightfield images
like fluorescence images. In the brightfield image the light passes through
the specimen and is absorbed by the different dyes. So the dye that appears
red would have absorbed mostly blue and green light, this means that the
red dye will be densest (in greatest quantity) at the places where there is
no blue or green light passing at all , this is wherever the blue or green
pixels are the darkest.
In your case the "meaningful" channel would be either BLUE or GREEN but NOT
RED. This is so, because the red appearing fibers would have absorbed this
colors and left red light pass true - that is why the red channel will be
less informative (in this channel you are actually quantifying the green or
blue stain which absorbed the red light).
That is why you will need to do the thresholding in one of these other
channels (chose the one in which the fibers seem denser (darker)). Next in
Analyze->Select measurements you should select Area and Area fraction with
the Limit to Threshold option checked. Then you run Analyze->Measure
(Ctrl+M) and you will receive total thresholded area in pixels and
Thresholded area fraction in %.
Another aproach would be to Invert the image and than quantify the
brightness in the Red channel of the Negative.
  Stoyan


2013/7/3 Benjamin Grant <[hidden email]>

> Running "subtract background" after threshholding will not do anything. Try
> running that first, then thresholding, that might be your issue.
>
> --
> 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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