Xu, F. et al. Cell Res. http://dx.doi.org/10.1038/cr.2015.160 (2016).
Typical single-molecule localization microscopy methods provide high-resolution images at the cost of speed, because many thousands of image frames are required to generate an image. Widefield-based super-resolution methods, such as Bayesian analysis of blinking and bleaching (3B), improve temporal resolution by using orders of magnitude fewer, densely labeled frames. Despite its potential, 3B utilization has been hindered by the time and computational cost of processing the data. Xu et al. have addressed this problem by developing single molecule-guided Bayesian localization microscopy (SIMBA), which achieves more efficient image processing. The new algorithms used in SIMBA also reduce image artifacts that can arise during 3B. The researchers used their method to generate high-quality images of labeled structures in fixed and live mammalian cells.