Posted by
Kevin Ryan on
URL: http://confocal-microscopy-list.275.s1.nabble.com/Deconvolution-advice-tp7579090p7579107.html
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**COMMERCIAL RESPONSE, MEDIA CYBERNETICS - AUTOQUANT **
Jay is correct that imaging modes such as SIM will not have PSFs matching ordinary microscopic modes. For deconvolving novel imaging methods such as SIM, the first and best approach is probably to use a fixed, measured PSF:
* Image a point object under the same conditions as your desired sample (and that includes your _embedding media_, as the refractive index of your media is a critical element of image formation!), then use that as a model for the system PSF. That should incorporate all elements of the imaging system in the transform between the point object and the observed PSF. The better the PSF image, the better final reconstruction will be.
As an example, AutoQuant has been used in this fashion for computed holographic microscopy (Rosen and Brooker 2008, "Non-scanning motionless fluorescence three-dimensional holographic microscopy",
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.153.3691&rep=rep1&type=pdf), with quite good results. The PSF for that system is notably _not_ a standard widefield or confocal blur.
* Blind deconvolution, where the PSF is optimized along with the data, _can_ be done with novel microscopic imaging modes by starting with a measured PSF and disabling PSF constraints (which are the constraints appropriate for widefield/confocal data - radial symmetry, energy conservation, etc). That would, however, be an experimental approach, and should be checked for ground truth against known specimens to see if it is appropriate for your data. Examine both the resulting deconvolution for known structures (did it remove blur, improve resolution?), and the resulting PSF for comparison to using SIM on a point object (does the final PSF have the general form of a measured point object?). This may provide a reconstruction improvement over a measured PSF by incorporating information from the observed sample.
Kevin Ryan
Media Cybernetics, Inc.
-----Original Message-----
From: Confocal Microscopy List [mailto:
[hidden email]] On Behalf Of Unruh, Jay
Sent: Tuesday, October 02, 2012 10:18 AM
To:
[hidden email]
Subject: Re: Deconvolution advice
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Hi all,
Deconvolution for SIM is a very different story than for other techniques. SIM by default uses an inverse filter in its reconstruction to recombine the shifted components of the fourier transform without enhancing the high frequency noise. Typical SIM software has a noise parameter for the wiener filter. If you set this filter low, you start to see a rippling pattern in the noise and eventually in the high signal regions. As far as I can tell, no one has tried to use more advanced (poisson noise driven) algorithms for this problem.
If one assumes that Autoquant is using some variant of the algorithm shown in Tim Holmes' Handbook of Biological Confocal chapter, then this algorithm is not immediately applicable to the SIM problem. The algorithm update function involves dividing the original image by the convolved object guess and then convolving that ratio with the reflected psf and finally multiplying by the object guess. Given that the raw SIM image is actually a frequency modulated image in a particular direction, it is not clear how the original ratio would be generated. Richardson-Lucy has a similar problem. Would you deconvolve before reconstructing? This is the only circumstance under which the noise could be considered poisson. In that case, can the original PSF be used? I'm not entirely certain that the deconvolution would preserve the frequency modulation in the image. In addition, the original reconstruction algorithm would require a second step of deconvolution during the reconstruction step--not sure how the noise parameter should be chosen after initial deconvolution.
Jay
-----Original Message-----
From: Confocal Microscopy List [mailto:
[hidden email]] On Behalf Of Gitta Hamel
Sent: Monday, October 01, 2012 8:42 AM
To:
[hidden email]
Subject: Re: Deconvolution advice
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**commercial response**
Hello Andrew,
It's fully understandable that people want to know the scientific grounds when using Huygens.
For the full list of articles I refer to
http://www.svi.nl/HuygensReferences at which the relevant papers are at the bottom of the page and mostly written during the years 1996-1998.
There are much more articles that ought to be included so your question shows that we must give more attention to this topic.
With best wishes,
Gitta Hamel
****************************************
Gitta Hamel
Managing Director Scientific Volume Imaging bv Developers of the *HUYGENS* software The Netherlands
phone: ++ 31 35 6 42 16 26
*****************************************
^SVI Customer support: mail us your questions
[hidden email] <mailto:
[hidden email]>or find answers online in our Huygens WIKI:www.svi.nl/FrontPage <
http://%20www.svi.nl/FrontPage>
On 09/29/2012 04:00 PM, Gens, John Scott wrote:
> *****
> To join, leave or search the confocal microscopy listserv, go to:
>
http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy> *****
>
> Andrew-
>
> You might want to get in touch with Jim McNally. Last I heard he was
> at NIH-NCI.
>
> Some of his older papers on deconvoltion algorithms are below, but he
> can probably point you towards more recent information.
>
>
http://www.ncbi.nlm.nih.gov/pubmed/10579932>
>
http://www.ncbi.nlm.nih.gov/pubmed/11541650 ( in particular, fig.2
> compared a 3D image processed by three different algorithms)
>
>
> Quoting Andrew York <
[hidden email]>:
>
>> *****
>> To join, leave or search the confocal microscopy listserv, go to:
>>
http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy>> *****
>>
>> Hello, I'm looking for advice and information about deconvolution,
>> especially from those with first-hand experience.
>>
>> Traditionally, one of the processing steps in structured illumination
>> microscopy is deconvolution. For our SIM, we decided to use an
>> open-source
>> solution:
>>
https://sites.google.com/site/piotrwendykier/software/deconvolution/p>> aralleliterativedeconvolution
>>
>>
>> This seemed like a nice tradeoff between reinventing the wheel with
>> our own deconvolution code, and subjecting ourselves to a 'black box'
>> closed-source
>> solution. However, we've recently tried out the Huygens deconvolution
>> software, and the results seem quite promising, possibly an
>> improvement over other methods we've tried. I like good images, but I
>> don't like black boxes, and I like to understand my data processing.
>>
>> 1. Is the exact algorithm used in Huygens transparently documented
>> anywhere? I spent a few hours searching today, but if it's out there,
>> I missed it.
>>
>> 2. Is there a clear winner for deconvolution algorithms? What should
>> I be using?
>>
>> 3. Are there other deconvolution software packages I should consider?
>> Ideally I'm looking for software based on clearly-documented algorithms.
>>
>> Thanks for the help.
>>
>> -Andrew York
>> NIH/NIBIB
>>
>
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