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The diffraction limit in light microscopy          

For centuries, people have been using light microscope to look at structures too small to see with human eye alone. However, since 1873, when Ernst Abbe first recognized the diffraction-limited resolution of light microscopes, researchers had been believing that any subcellular structures smaller than ~200 nm are unresolvable by light microscopes.






Super-resolution localization microscopy breaks the resolution limit          

In 2006, a new kind of light microscopy called super-resolution localization microscopy was invented to break the diffraction limit. Currently, super-resolution localization microscopy is capable of offering spatial resolution 10 times better than conventional light microscopy, and thus provides unprecedented opportunities for tackling outstanding fundamental problems in life science, medicine, materials, chemistry, etc.






Big data challenges in super-resolution localization microscopy          

The remarkable gain in the spatial resolution of super-resolution localization microscopy relies on stochastically activating sparse subsets of densely labelled fluorophores and subsequently determining their positions. Typically, thousands or even tens of thousands of raw camera images are necessary to reconstruct a final super-resolution image. Therefore, a massive amount of data needs to be processed (including transfer, store, and analyze) in super-resolution localization microscopy, especially with the advantageous use of better-performing sCMOS cameras which offer simultaneously large field of view and extremely fast frame rates and thus generate up to 3.0 terabytes data in accumulative one-hour imaging.






We aim to pick up useful data rather than big data:




1) Algorithms, software and hardware platforms for massive data processing in super-resolution localization microscopy:      

To overcome the challenges of massive data processing (including transfer, store, and analyze) in super-resolution localization microscopy, which are troublesome for classical EMCCD cameras and are thought to bring great growing pains for better-performing sCMOS cameras, we are working to develop efficient data processing algorithms, user-friendly software and hybrid-computing platforms.

2) Selection and optimal use of low-light cameras for super-resolution localization microscopy:

The selection and optimal use of low-light cameras is important but also confusing in super-resolution localization microscopy. We are currently working with several camera manufactures to evaluate and understand the imaging performance of low-light cameras, and try to offer a guide to the selection and optimal use of low-light cameras for single molecule imaging and super-resolution localization microscopy.

3) Enhancing the power and versatility of super-resolution localization microscopy:

We are working to enhance the power and versatility of the technique: super-resolution localization microscopy with large field-of-view, super-resolution localization microscopy for tracing and visualizing neuronal circuits, video-rate super-resolution localization microscopy. We are also working with chemists to develop new super-resolution probes, and biologists to study fundamental questions in life sciences.






   





 
Britton Chance Center for Biomedical Photonics |1037 Luoyu Road, Wuhan, China, Huazhong University of Science & Technology | Tel:(027)87792033 | Fax:(027)87792034