Thanks to the advent of super-resolution microscopes some 30 years ago, scientists can observe subcellular structures, proteins, and living tissue with unprecedented precision. These microscopes operate by measuring the fluorescent light that some compounds emit naturally or the light emitted by artificial fluorophores. And by exploiting various quantum properties of the fluorophore, they can deliver a resolution smaller than the one imposed by the diffraction limit.
However, a problem with these microscopes is that image quality varies considerably depending on the particular instrument being used, its settings (such as how powerful the laser is and how the individual components are aligned), and the proprieties of the sample being studied. But in a study published today in Nature Methods, a team of EPFL scientists developed an algorithm that can estimate a microscope’s resolution in just a few seconds based on a single image.
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The scientists used Fourier’s transform as the basis for their algorithm, but they modified it so as to extract as much information as possible from a single image. The results indicate how closely a microscope is operating to its full potential. The algorithm performs the calculation in just a few seconds and generates a single number.
“Researchers can compare this number with the microscope’s maximum possible resolution to see whether the instrument can work even better or modify the experimental conditions and observe how the resolution evolves,” says first author Adrien Descloux.
The algorithm can be used with any kind of imaging modality, including super-resolution models. “Our technique is particularly promising for the emerging generation of automated microscopes, where a computer adjusts all their settings,” says senior author Aleksandra Radenovic.
The algorithm has been made available as an open-source image plugin. Researchers can download the tool and directly obtain the algorithm estimate, showing them how closely their microscope is operating to its maximum resolution.
“Our algorithm is universal. And because only one image is needed, it is particularly suited for fast optimization of imaging conditions, which is challenging when observing dynamic processes,” says Descloux. “Also, the method can be applied in the image processing, as feedback for optimization of the advanced image reconstruction algorithms.”
Image: The results indicate how closely a microscope is operating to its full potential. Image courtesy of EPFL.