Posted by
Tim Feinstein on
URL: http://confocal-microscopy-list.275.s1.nabble.com/General-question-Software-vs-hardware-tp7589316p7589334.html
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Hi Alison,
The signal to noise question strikes me as the key question WRT decon. Most software packages default to a setting that seems unrealistic for confocal imaging (ie SNR=20), and this leads to a lot of patterning artifacts in deconvolved images. At such high SNR any pixel of data is treated as 'real', so background noise gets processed into weird moire-type patterns. This also happens when the algorithm doesn't quite converge and you let it run for too many iterations (the default iteration #s tend to be set high as well). It's critical then to tell the software (when possible) that your SNR is low, so it gets much more aggressive about detecting and removing random noise (at the expense of losing details in the 1-3 pixel range). I would recommend folks take care if using any package that doesn't let you correct the SNR.
Honestly, when SNR is set properly I find that noisy images benefit a lot more from decon than high-quality cover candidate-type pics. In addition to sharpening and Z blur removal the noise and background removal becomes more dramatic (and beneficial for quantitation) the more background and noise there is. This comes up a lot when live imaging when we use resonant scanning for speed and low photodamage, but have higher noise as a trade-off. I'd say that as long as you can image at 1.5x-2x Nyquist resolution (and the extra time/expense is worth it), even super-noisy images will benefit quite a bit.
I understand that we're crossing fingers for the day when everyone has GPU-enabled decon running seamlessly during acquisition. For that to work the algorighms need to automatically (accurately) estimate SNR. That doesn't seem like an insurmountable challenge, but I haven't seen it yet.
Best,
TF
Timothy Feinstein, Ph.D.
Research Scientist
Department of Developmental Biology
University of Pittsburgh
On 3/18/19, 11:07 AM, "Confocal Microscopy List on behalf of Alison North" <
[hidden email] on behalf of
[hidden email]> wrote:
Hi all,
So this is a very timely discussion because I have been discussing with
my staff whether there are data sets that should NOT be deconvolved, and
if so, how does one decide that? I too attended Jim Pawley's wonderful
course (he was certainly a huge character as well as an incredibly
fantastic microscopist, and he will certainly be remembered by all!), so
I have generally worked under the assumption that one should deconvolve
all confocal data. But I am also very aware of the potential for
artifacts if a data set isn't "good enough" for deconvolution.
Obviously the ideal situation is to acquire an optimal data set -
well-prepared sample, bright staining, Nyquist sampling etc. etc., and a
high S:N ratio - and by sticking to these rules, our deconvolved
DeltaVision images or confocal images of fixed samples have always
looked great. But nowadays we are faced with different scenarios,
particularly when you are attempting to do very rapid imaging of live,
weakly expressing cells, while attempting to minimize phototoxicity. In
that case you can end up with pretty lousy S:N ratios, because
maintaining cell viability or imaging fast enough is more critical.
For example, I have a lovely new iSIM in my lab, for which the initial
resolution increase is achieved by the hardware, but the second step in
resolution increase is via deconvolution. The whole point of this
instrument is for rapid, super-resolution imaging - so we can't simply
increase exposure times to improve S:N, turning up the laser power will
obviously kill the cells, and we can't increase the pixel size or we'll
lose the resolution. And I assume a lot of the new types of
super-resolution instrument out there must leave you facing the same
issue, since live cell imaging invariably forces you to compromise
somewhere within the imaging triangle (or hexagon, or whatever we've got
up to now!).
Therefore my question is, are there papers out there which have compared
deconvolution algorithms and looked at the potential for artifacts on
really low S:N images, which we could use to advise our researchers on
what is the minimum you can get away with before you really shouldn't be
deconvolving the data set at all? Also, are there papers showing the
effect of undersampling in the z-axis on the resulting deconvolved
images (as is often the case on our spinning disk system)? I haven't
managed to find any yet (though I confess I've been too busy with other
stuff to spend too many hours searching!), so if anybody could point me
to some good references I'd be most grateful. I have spoken with
several renowned microscopists about whether deconvolution is always a
good idea under such circumstances, and the gut reaction appears to be
no, but I could do with some hard and fast validation for teaching purposes.
Many thanks in advance!
Alison
On 3/18/2019 9:56 AM, Feinstein, Timothy N wrote:
> *****
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>
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> *****
>
> Avi, I really agree with your point. I feel that people to deconvolve any time spatial information is critical, whether they're using widefield, CLSM, spinning disc, or light sheet. It's true that deconvolving adds time and data volume and especially cost, but in trade you get an image that is substantially sharper, with reduced noise and background, and more quantitatively accurate*.
>
> Regarding whether to just go with a point scanning confocal, I don't see it as a simple question of better or worse**. A nuclear-cytoplasmic translocation assay with monolayer cells works just as well on a widefield, and (in my experience!) many types of biosensor assay work better with a properly set up widefield. The 16-bit depth of widefield images is nice for quantitation, and modern sCMOS cameras have by far the best acquisition speeds. I don't know whether widefields still have a more linear relationship between sample brightness and detected signal, but the last time I checked that was still true.
>
> (*) Deconvolution is quantitatively useful as long as people make sure to tell the software to preserve the original intensity values. One of my complaints about Hyvolution was that you could not do that, so I just used the Huygens package that came with it. I don't know whether Lightning gives you that option...if not then caveat emptor.
>
> (**) My advice mostly applies to turnkey stuff that any lab can implement, not exotic techniques available to folks with specialists or engineers on hand.
>
> Best,
>
>
> T
> Timothy Feinstein, Ph.D. esearch Scientist
> Department of Developmental Biology
> University of Pittsburgh
>
>
> On 3/18/19, 5:07 AM, "Confocal Microscopy List on behalf of Avi Jacob" <
[hidden email] on behalf of
[hidden email]> wrote:
>
>
> I'll point out, that you can, of course, deconvolve confocal images too.
> So, while you can indeed get near confocal quality with well-acquired wf
> data after deconvolution, you can also get near SR quality when
> deconvolving a well-acquired stack from a confocal. And then you can also
> deconvolve a SR stack and get... well you get the idea! It's like an arms
> race.
> I have the Hyvolution and had access for a couple of weeks to the Lighting,
> and now confocal images look blurry to me.
> Avi
>
> --
> Avi Jacob, Ph.D.
> Kanbar Light Microscopy Unit
> The Mina & Everard Goodman Faculty of Life Sciences
> Bar-Ilan University, Ramat-Gan 529002, Israel
>
>
>
> On Sun, Mar 17, 2019 at 6:04 PM George McNamara <
[hidden email]>
> wrote:
>
> > *****
> > To join, leave or search the confocal microscopy listserv, go to:
> >
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> > *****
> >
> > Hi Mika,
> >
> > White et al 1987 (
https://nam05.safelinks.protection.outlook.com/?url=https%3A%2F%2Furldefense.proofpoint.com%2Fv2%2Furl%3Fu%3Dhttps-3A__nam05.safelinks.protection.outlook.com_-3Furl-3Dhttp-253A-252F-252Fjcb.rupress.org-252Fcontent-252F105-252F1-252F41.long-26amp-3Bdata-3D02-257C01-257Ctnf8-2540PITT.EDU-257Ce2895884dda94858a22408d6ab8114ff-257C9ef9f489e0a04eeb87cc3a526112fd0d-257C1-257C0-257C636884968257860747-26amp-3Bsdata-3Da6oZCfeD7Gt4nYMS89PcklnveCdDLLkksafp3tCyld0-253D-26amp-3Breserved-3D0%26d%3DDwIGaQ%26c%3DJeTkUgVztGMmhKYjxsy2rfoWYibK1YmxXez1G3oNStg%26r%3DRBx0-WJrAO5vwSOLNmFbqYvikvIZS5ns3-USwvMOuLo%26m%3DjqVgS0XjNSmttSUahDdaDaAsBeK67RlyWHCj8N7ZMJw%26s%3D67LyqPF2rBiBDSWJVZeG7TpJz1o4MRDf8ZyLysbeKx4%26e&data=02%7C01%7Ctnf8%40PITT.EDU%7Cdc51ccda0c794046d93408d6abb362a8%7C9ef9f489e0a04eeb87cc3a526112fd0d%7C1%7C0%7C636885184288894390&sdata=R3V0RHiTDpGkJUJyI8Q7SDJZjKdk3uDMgmBEPLrzcUw%3D&reserved=0= ) made a
> > compelling case for point scanning confocal microscopes: collect just
> > the in focus light with instant gratification. The case has not changed,
> > the hardware (especially data deluge side) has gotten a lot better. I
> > note that both widefield detectors and PMT/APD/hybrid detectors/others
> > have gotten a lot better in the 32 years from 1987! As have the optics
> > and automation.
> >
> > Paul Goodwin 2014 (
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> > a nice case for quantitative deconvolution microscopy (and on very high
> > quality specimens, ~10% improvement in resolution compared to simple
> > widefield), but historically slow.
> >
> > Now, with 'instant gratification' spatial deconvolution, thanks to the
> > GPU revolution (NVidia RTX Titan~16 Teraflops [S.P.], 24 Gb ram, $2500
> > ... not including the deconvolution software module price), widefield,
> > spinning disk (and slightly exotic variants like iSIM, DMD based, etc,
> > see also new THUNDER Imagers [see p.p.s.]), multiphoton (I'm excited
> > about the price point of recent fiber lasers, which could become much
> > better price if achieve 'economy of scale'), and of course, point
> > scanning confocal microscopes.
> >
> > Spatial deconvolution (especially if someone $uccessfully implements
> > joint spatial deconvolution and spectral unmixing, multiple cameras -
> > for 4 cameras see Babcock 2018, mentions aiming for 8 cameras) helps
> > with Expansion Microscopy and/or DNA-PAINT, to go super-resolution ...
> > really single molecule counting (and DNA-PAINT eliminates the classic
> > issue of PALM/STORM/FPALM of not counting every molecule). Sure,
> > DNA-PAINT (like STORM etc) have the issue of a whole lotta images
> > acquired. Data deluge: who cares? Jerome & Price's 10th commandment of
> > confocal imaging is: "10. Storage Media Is Essentially Free and Infinite".
> >
> > More significantly, DNA-PAINT and related methods (single molecule RNA
> > FISH, scRNAseq -> MERFISH = Moffitt 2018 as example, etc) also enable
> > multiplex -- with single molecule counting -- to whatever plex is needed
> > to answer the 'biological question(s)' being posed.
> >
> > All that said, the installed base of research grade point scanning
> > confocal microscopes is large (5000+) and efficient at acquiring high
> > quality images, to the point that user's sample preparation (and
> > avoidance of purchasing stuff from 'Santa Crap' and similar companies)
> > is much more limiting than the microscopes.
> >
> > George
> >
> > p.s. a couple of references not included in above:
> >
> > W. Gray (Jay) Jerome, Robert L. Price 2018... Basic Confocal Microscopy
> > second edition
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> > Expansion ... X10 protocol ... Truckenbrodt 2019 Nat Protoc,
> >
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> > DNA-PAINT acronym soup review ... Nieves 2018 Genes,
> >
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> > Babcock 2018 (4 --> 8 cameras, single molecule localization microscopy
> > with $1550 CMOS cameras) ...
> >
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> > Moffitt et al 2018 ...
> >
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> > commentary
https://nam05.safelinks.protection.outlook.com/?url=https%3A%2F%2Furldefense.proofpoint.com%2Fv2%2Furl%3Fu%3Dhttps-3A__nam05.safelinks.protection.outlook.com_-3Furl-3Dhttp-253A-252F-252Fscience.sciencemag.org-252Fcontent-252F362-252F6416-252F749-26amp-3Bdata-3D02-257C01-257Ctnf8-2540PITT.EDU-257Ce2895884dda94858a22408d6ab8114ff-257C9ef9f489e0a04eeb87cc3a526112fd0d-257C1-257C0-257C636884968257870756-26amp-3Bsdata-3Do0B379uuh-252FrB6gS9n6lG-252BjAZeztiYHZVmICwX4ghKh8-253D-26amp-3Breserved-3D0%26d%3DDwIGaQ%26c%3DJeTkUgVztGMmhKYjxsy2rfoWYibK1YmxXez1G3oNStg%26r%3DRBx0-WJrAO5vwSOLNmFbqYvikvIZS5ns3-USwvMOuLo%26m%3DjqVgS0XjNSmttSUahDdaDaAsBeK67RlyWHCj8N7ZMJw%26s%3DXeBps6CWTMM197evmy1n1uC5qOcvU8mAN95bEPmieiQ%26e&data=02%7C01%7Ctnf8%40PITT.EDU%7Cdc51ccda0c794046d93408d6abb362a8%7C9ef9f489e0a04eeb87cc3a526112fd0d%7C1%7C0%7C636885184288904398&sdata=um%2F%2FPNffQLOyrTsQcJymSuR2XwRcVnNMwMgQ6qYy19A%3D&reserved=0= > >
> > ***
> >
> > Some resolution numbers:
> >
> > 1.4 NA objective lens ... 500 nm wavelength .. dxy = 0.61 * wqavelength
> > / NA (I routinely drop the 0.61 from 0.61)
> >
> > 0.6 * 500 / 1.4 = 214 nm
> >
> > widefiel deconvolution (re: Goodwin 2014) ~10% better ... 193 nm (if
> > pixel size matched or interpolate optimally).
> >
> > point scanning confocal -- Zeiss has a nice PDF, "Zeiss 2008 Principles
> > - Confocal Laser Scanning Microscopy" (see fig 10) on confocal
> > resolution wrt 1 and smaller pinhole size, source of the values below,
> >
> > 1 Airy unit: 0.51 * 500 / 1.4 = 182 nm.
> >
> > 0.5 Airy unit ... 0.44 * 500 / 1.4 = 157 nm ... ~0.25 photons throughput
> > (which doesn't matter if target is photostable).
> >
> > 0.2 Airy unit ... you can ask your Zeiss rep about AiryScan (and
> > FastAiryScan).
> >
> > 0.1 Airy unit ... 0.37 * 500 / 1.4 = 132 nm ... ~0.10 photons throughput.
> >
> > Most modern point scanning confocal microscopes have a 405 nm laser, so
> > if using BV421 (and ignoring potential photobleaching for a moment),
> >
> > 1 Airy unit: 0.51 * 421 / 1.4 = 153 nm.
> >
> > or in reflection mode, i.e. nanodiamond or nanogold,
> >
> > 1 Airy unit: 0.51 * 405 / 1.4 = 147 nm ... and reflection implies no
> > photobleaching, so infinite number of photons (though also no blinking,
> > so not usually eligible for precision localization) ...
> >
> > 0.1 Airy unit: 0.37 * 405 / 1.4 = 107 nm
> >
> > and not going completely exotic with NA (i.e. 1.65), if perfectly
> > refractive index match with a fairly conventional 1.49 NA lens, and
> > inreflectance:
> >
> > 0.1 Airy unit: 0.37 * 405 / 1.49 = 100.57 nm
> >
> > I think I'd rather invest a DNA-PAINT friendly rig than deal with 157 to
> > 101 nm.
> >
> > DNA-PAINT makes resolution irrelevant, if you use it (and don't run out
> > of disk space or time or money), since precision localization is
> > resolution divided by square root of number of photons, ex. 250 nm XY
> > resolution / sqrt(1,000,000) = 0.25 nm, and could increase number of
> > photons per target further, but why bother?
> >
> > ***
> >
> > point scanning confocal microscopes are also great platforms for
> > F-Techniques, such as FastFLIM (aka rapidFLIM, etc, much faster than
> > classic TCSPC slow FLIM), FCS, FCCS, see Liu 2008,
> >
https://nam05.safelinks.protection.outlook.com/?url=https%3A%2F%2Furldefense.proofpoint.com%2Fv2%2Furl%3Fu%3Dhttps-3A__nam05.safelinks.protection.outlook.com_-3Furl-3Dhttps-253A-252F-252Fwww.ncbi.nlm.nih.gov-252Fpubmed-252F18387308-26amp-3Bdata-3D02-257C01-257Ctnf8-2540PITT.EDU-257Ce2895884dda94858a22408d6ab8114ff-257C9ef9f489e0a04eeb87cc3a526112fd0d-257C1-257C0-257C636884968257870756-26amp-3Bsdata-3DZQTosrSoPFpCa8Y3IdEa9Xz-252B4RHC8JO4gBppHmzkazo-253D-26amp-3Breserved-3D0%26d%3DDwIGaQ%26c%3DJeTkUgVztGMmhKYjxsy2rfoWYibK1YmxXez1G3oNStg%26r%3DRBx0-WJrAO5vwSOLNmFbqYvikvIZS5ns3-USwvMOuLo%26m%3DjqVgS0XjNSmttSUahDdaDaAsBeK67RlyWHCj8N7ZMJw%26s%3DmeRUIZdF3FLQZGyok4cxyc4AP4yq2lXX41Vt8q9WMmw%26e&data=02%7C01%7Ctnf8%40PITT.EDU%7Cdc51ccda0c794046d93408d6abb362a8%7C9ef9f489e0a04eeb87cc3a526112fd0d%7C1%7C0%7C636885184288904398&sdata=XTEH306i5ez7vKq2cHKCVQlSphNiFIdnqIXmwnOmyNw%3D&reserved=0= > >
> > ***
> >
> > p.p.s. Disclosures I am ...
> >
> > 1. currently hosting a Leica THUNDER Imager tour event (ends Monday
> > 3/18/2019 afternoon) ... see pdf download page,
> >
> > THUNDER Technology Note
> > THUNDER Imagers: How Do They Really Work?
> >
> >
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> > 2. hosting Nikon confocal demos in May 2019.
> >
> > 3. aiming to co-host with ISS a FastFLIM (one day) mini-symposium this
> > summer.
> >
> > 4. an unpaid advisor for Gary Brooker for FINCH/CINCH, re:
> >
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> >
> > On 3/17/2019 10:43 AM, Mika Ruonala wrote:
> > > *****
> > > To join, leave or search the confocal microscopy listserv, go to:
> > >
https://nam05.safelinks.protection.outlook.com/?url=https%3A%2F%2Furldefense.proofpoint.com%2Fv2%2Furl%3Fu%3Dhttps-3A__nam05.safelinks.protection.outlook.com_-3Furl-3Dhttp-253A-252F-252Flists.umn.edu-252Fcgi-2Dbin-252Fwa-253FA0-253Dconfocalmicroscopy-26amp-3Bdata-3D02-257C01-257Ctnf8-2540PITT.EDU-257Ce2895884dda94858a22408d6ab8114ff-257C9ef9f489e0a04eeb87cc3a526112fd0d-257C1-257C0-257C636884968257870756-26amp-3Bsdata-3DdHOCjeBda4sSZPf-252FB2-252B5Sv3Q8Qzcs708p4we8vHf-252FIg-253D-26amp-3Breserved-3D0%26d%3DDwIGaQ%26c%3DJeTkUgVztGMmhKYjxsy2rfoWYibK1YmxXez1G3oNStg%26r%3DRBx0-WJrAO5vwSOLNmFbqYvikvIZS5ns3-USwvMOuLo%26m%3DjqVgS0XjNSmttSUahDdaDaAsBeK67RlyWHCj8N7ZMJw%26s%3DqZ-tdRwhHG172zv4uHPeAJMNeIIHNxozhQudV-hF2kE%26e&data=02%7C01%7Ctnf8%40PITT.EDU%7Cdc51ccda0c794046d93408d6abb362a8%7C9ef9f489e0a04eeb87cc3a526112fd0d%7C1%7C0%7C636885184288904398&sdata=BnCAxorVJgPSFw70Kr%2B401vq4hMlZhvzdkivum9XGNE%3D&reserved=0= > > > Post images on
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> > posting.
> > > *****
> > >
> > > Hi.
> > > There are software solutions that are able to create image data from
> > wide-field and even microscope systems with seemingly similar quality to
> > that obtained from confocal systems.
> > >
> > > The comparison of acquisition vs. software is essentially a comparison
> > of image acquisition vs. image processing. While a software solution is way
> > cheaper than a hardware solution if it is able to produce image data with
> > equal quality why would anyone choose to invest to a confocal anymore?
> > >
> > > I’m looking forward to a vidid discussion!
> > >
> > >> m
> >
>
>
--
Alison J. North, Ph.D.,
Research Associate Professor and
Senior Director of the Bio-Imaging Resource Center,
The Rockefeller University,
1230 York Avenue,
New York,
NY 10065.
Tel: office ++ 212 327 7488
Tel: lab ++ 212 327 7486
Fax: ++ 212 327 7489