[OpenSPIM] Multiview Reconstruction- optimizing settings?

[Anthony, Neil]

Hi Maarten, I hope the science treats you well.

When I get a registration result that works I feel the overlap in the BDV looks good, although this is a little subjective.  Can I ask what kind or errors you get in the log during the registration?  I've found that I can get it down to less than a pixel and it looks ok.*, **

I find that the allowed pixel error helps (I use 1 px), and the significance is less sensitive, but I've found 10-15 appears better.  Following that the lambda value is better when higher as far as I can tell.  I started to look into the literature, but these things are not so accessible on just skimming the papers.

I don't know how much the transformation model and model to regularize with affects things as I haven't played with those much.  Also, I don't know how the sigma values and thresholds of the bead detection affect the registration, if at all.

Thanks
Neil

* I have a camera that is not properly sampling. I've opted to get a larger area and sacrifice resolution on the old ORCA's we're using. I have a pixel spacing of 0.64 um, which is approximately the resolution with the 20XW lens.  Can I ask if anybody knows how my resolution is affected?  I assumed that doubling the field of view in this way would leave me with a resolution ~ 1um...?
** My calibration samples, registrations, and MVdecons are looking pretty nice, but I'm struggling with the real world samples for some reason...  I topic for another post once I've tried a few things.



From: OpenSPIM [mailto:openspim-bounces at openspim.org] On Behalf Of Maarten Hilbrant
Sent: Monday, August 22, 2016 9:26 AM
To: openspim at openspim.org
Subject: [OpenSPIM] Multiview Reconstruction- optimizing settings?

Dear all,

nice to see some questions on the mailing list lately regarding Stephan Preibisch' multview plugin. After attending the EMBO workshop in Dresden in 2014,  I've been using the plugin for two years now and it is an essential part of our light sheet workflow. In a nutshell, we image insect embryos, embedded in agarose containing sub-resolution beads, using single-sided illumination with 8 or 16 angles per time point. In order to infer the biological relevance of RNAi phenotypes, we tend to look at many different specimens for few time points, rather than collecting time-lapse data for a small number of specimens. In practice, this means a lot of reconstructing and adjusting settings, although I find that, for most of our datasets, default settings work nicely for bead detection, registration and deconvolution ("Nicely" in this case meaning a significant increase in local contrast). Sometimes, however, registration is sub-optimal (and who knows, maybe it is also for the analyses that I normally quality as "nice''-). In these cases, as a first hint, inspection with the BigDataViewer reveals that the psf's of the different angles don't overlap properly.

- Does this sound familiar to other users of the plugin?
- What reconstruction parameters do you generally tinker with first?
- for example: do you spend a lot of time on bead detection (and subsequent exclusion)?
- Do you sometimes reject datasets for multi view reconstruction and if so, on what grounds? For example, I like to image "a lot" of agarose surrounding the embryo in order to have a large set of beads for reconstruction, but am not always very systematic about this. Is this crucial in your data acquisition?

any ideas appreciated, basically to make better use of this great tool.

cheers,
Maarten

******************************
Dr. Maarten Hilbrant
Postdoctoral Researcher
Zoological Institute
University of Cologne
Cologne Biocenter
Zülpicher Str. 47b
50674 Cologne
Germany
+49(0)221-4703238
m.hilbrant at uni-koeln.de<mailto:m.hilbrant at uni-koeln.de>



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