Re: Deconvolution of Confocal Images? (was: Airy Units)

Posted by James Mansfield on
URL: http://confocal-microscopy-list.275.s1.nabble.com/Deconvolution-of-Confocal-Images-was-Airy-Units-tp6947651p6948488.html

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Hi,

I'm not sure I like calling out-of-focal-plane photons "noise". They are not noise, they are just signals from places where you don't happen to want them at the moment.

To take a set of terms from another field, the military hyperspectral imaging crowd (who are generally trying to isolate the signal from a tank or other military object from the background of normal non-military objects) have come up with:

Noise: random or instrument signals that are an artifact of the way you collected the data
Signal: the signal you actually care about
Clutter: other (real) signals that interfering with your ability to see the signal

Depending on the sample, either "noise" or "clutter" are the limiting factors. For many samples looked at in confocal, noise is the limiting factor. For many highly autofluorescent tissue samples, clutter is the limiting factor and needs to be dealt with differently than random noise.

Jim



James R. Mansfield
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-----Original Message-----
From: Confocal Microscopy List [mailto:[hidden email]] On Behalf Of Guy Cox
Sent: Monday, October 31, 2011 7:21 AM
To: [hidden email]
Subject: Re: Deconvolution of Confocal Images? (was: Airy Units)

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Daniel White wrote:

" in a confocal you throw away most of the signal, as its out of focus.
So as a result the images are often very noisy.  "

This is often stated but IT IS TOTALLY UNTRUE.  What is out of focus is
noise, not signal.  If you have no SA (and, honestly, if you are
seriously interested in high-resolution imaging that should be a given)
then a confocal microscope with the pinhole set at 1 Airy diameter
throws away no signal at all.  So why are confocal images often noisy?
Well, it's just statistics.  If you take a wide-field image with a 1
second exposure each point is exposed for one second.  If you take a
confocal image at 512 x 512 for 1 second then each point is exposed for
~4 microseconds.  The difference is rather substantial ...

                                           Guy

Optical Imaging Techniques in Cell Biology
by Guy Cox    CRC Press / Taylor & Francis
     http://www.guycox.com/optical.htm
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Australian Centre for Microscopy & Microanalysis,
Madsen Building F09, University of Sydney, NSW 2006

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-----Original Message-----
From: Confocal Microscopy List [mailto:[hidden email]]
On Behalf Of daniel white
Sent: Monday, 31 October 2011 8:30 PM
To: [hidden email]
Subject: Deconvolution of Confocal Images? (was: Airy Units)

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Hi Peter,

On Oct 31, 2011, at 6:02 AM, CONFOCALMICROSCOPY automatic digest system
wrote:

>
> Date:    Sun, 30 Oct 2011 13:09:10 -0700
> From:    Peter Werner <[hidden email]>
> Subject: Deconvolution of Confocal Images? (was: Airy Units)
>
> An interesting point was made here by Jim Pawley:
>
>> I agree that sampling a bit higher than Nyquist never hurts,
>> especially if you deconvolve (as you always should), but I think
>> that it is a mistake to think that one can "separate" out the noise
>> by decon. I think that noise is pretty fundamental.
>
> I had always heard that if you're doing confocal microscopy, at least

> point-scanning confocal with a pinhole size of 1AU or smaller, that
> deconvolution was superfluous, because you shouldn't be getting out of

> focus light. So what is gained by deconvolution when one is sampling
> voxel by voxel?

in a confocal you throw away most of the signal, as its out of focus.
So as a result the images are often very noisy.
Good contrast.... but high Poisson distributed photon shot noise
from only measuring a handful of photons.

So usually one needs to do something about that noise...
we want to separate the real signal from the noise.

Often a Gaussian or mean filter is applied... which suppresses the noise

by smoothing it out... but it also smooths the real signal, so
effectively you lose
the contrast and resolution that was the whole point of doing confocal.

The smart way to suppress the noise, but keep the contrast and
resolution
is to do deconvolution.
Deconvolution using a max likelyhood method uses the known shape of the
PSF
to make a best guess model of the real fluorophore distribution in the
sample.
You tell the deconvolution algorithm how noisy the image is (you have to
guess
unless you take 2 images and measure it)
then it attempts to throw out the noise and keep the real signal,
resolution and contrast intact.

D

>
> Peter G. Werner
> Merritt College Microscopy Program

Dr. Daniel James White BSc. (Hons.) PhD

Leader - Image Processing Facility,
Senior Microscopist,
Light Microscopy Facility.

Max Planck Institute of Molecular Cell Biology and Genetics
Pfotenhauerstrasse 108
01307 DRESDEN
Germany

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