Bayes methods have come to microscopy. Researchers have developed the Bayesian analysis of photo-blinking and photo-bleaching in microscopy to deduce the structure that is not usually visible. (Bayesian localization microscopy reveals nanoscale podosome dynamics, Cox, S et al, Nat. Methods 9, 195 (2012)) http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.1812.html
There have been many methods that are used for super resolution and some of them involve using severely modified microscopes. There are many advantages and disadvantages to each method but the one that has gained most attention is the published method. This method is available as an open source software for computation for everyone under the GPL license. This method is also available as a plugin in ImageJ at the link below so do try it out with your images.
This 3B method first measures the light emitted by the fluorophores as they undergo photobleaching and blinking in multiple frames. These images are then analyzed using Hidden Markov Model that allows Bayesian prediction for the presence of overlapping flourophores.
This method is computationally intense. In a Feb 2013, Nature article it was pointed out that with a typical pixel size of 100 nm, the analysis of 1.5 micron square area with 200 frames will take about 6 hours. However, this will allow the super-resolution microscopy with conventional microscopes even those equipped with Xenon lamp illumination – no lasers required.
There are a few requirements for this method to work:
- Structures to images should be less than 500nm and at a low enough density
- Reducing agents are required to be incorporated for organic dyes to induce blinking
- Data should be recorded with a low noise camera for good signal/noise ratio.
This method is thus able to resolve structures that were previously not possible.
