At our research facility we routinely perform what are called PALM (Photo-activated localisation microscopy) or STORM (stochastic optical reconstruction microscopy) experiments.You can read all about it in the links above but in short it boils down to this:Normal optical microscopy is diffraction limited. We can only resolve features bigger than say 200-300 nm because of the very nature of the wavelengths and optics we use.We can circumvent this resolution limitation by finding ways to observe point emitters in a sample and using what is known about their point spread function to fit the location of those emitters with sub diffraction limit accuracy.Observing many such point emitters in a sample allows us to reconstruct an image of the entire sample with enhanced resolution.Practically, we achieve all this by recording long (50k frames) movies of samples using EM-CCD cameras which produce 16 bit 512*512 pixel images. As such, these datasets grow quite big, particularly if we run lots of experiments daily/weekly.Next we run established fitting routines on these datasets, such as the ones implemented here.Currently we do all this in what I call Offline mode. We record these data sets, often dozens or hundreds of times a week. Store them on USB hard drives and run the above referenced analyses.This leads to issues:Yearly, we invest thousands of euros in disks because we need to store all erudite and might want to hang on to it for future reference. However, this data cannot be properly indexed and managed. Everyone uses their own schemes for naming/folders/...Disks can go missing...Reading so much about cloud computing lately, I wanted to try and find better solutions to the issue. I think that it should be possible to:Install some kind of Dropbox like client on each measurement computer.Upload all raw image stacks to a cloud storage facilityExpose that cloud storage as a virtual disk to nice software such as The Open microscopy Environment which already offers solutions for indexing/annotating ur type of dataLeverage the computational power of cloud systems to also speed up the analysisIn this respect I have contacted several cloud providers (MS Azure, Google, Amazon) but in my experience it is very hard to get in touch with someone knowledgable enough to first get our intended application and next to provide viable potential solutions.Furthermore, although I grasp most of the concepts involved in modern cloud platforms I lack the time and in depth knowledge to roll my own solution.Nonetheless I cannot imagine that we would be the first people to run into this issue.Does anybody have an idea in this respect?DISCLAIMER: It could be that this question is out of scope for this particular SA site but I did not seem to find another where this would be better suited (or I missed it).
Cloud solutions for microscopy image analysis
image processing;data management;cloud computing