Current super-resolution microscopy techniques require special laser setups and fluorescent molecules (such as PALM and STORM) that allow the fluorophores to be turned on and off so that only a small number of fluorophores are turned on at any time. With the Super Shrimp image analysis algorithm, super-resolution images can be created from images with high densities of fluorophores. The invention creates microscopy images that have 5 or more times better resolution than standard microscopy images while using the standard microscopic set up available in most laboratories. It allows use of any fluorescent molecule (including quantum dots) that blinks or photobleaches to pick fluorophores out of the fluorescent background, and it can work with thousands of fluorophores in an image.
This image analysis algorithm can localize quantized drops in fluorescence even with a background to create super-resolution images from standard photobleaching movies. It does not require special photo-switchable fluorophores (PALM, STORM) or fluorophores with long-lived dark states (dSTORM). The data acquisition is accomplished in minutes instead of hours and it can use standard laboratory microscopic set up with any fluorescent molecule. The algorithm processes a movie in which fluorescent molecules or particles are photobleaching or blinking and looks for individual photobleaching events that can be located with high resolution (i.e. the position of the fluorescent molecules). A composite image with resolution much higher than the original movie can then be generated.
Noise is reduced by rejecting fluorophores that are poorly fit by a Gaussian and frames are averaged.
The image analysis algorithm to create super-resolution images using standard photobleaching and blinking movies provides the following benefits:
- Uses standard laboratory equipment.
- Enables sub-cellular structure examination
- Can be used with any fluorescent molecule that can be detected by a CCD camera. It can use high labeling densities
- Fast data acquisition