ABOVE: A deep neural network enabled the conversion of confocal images of HeLa cell nuclei (left) to super-resolution images (middle) comparable to those achieved using the super-resolution imaging technology known as stimulated emission depletion (right).
OZCAN LAB AT UCLA
Using a type of artificial intelligence, scientists have turned lower-resolution micrographs of cells into high-quality images of the sort typically achieved using super-resolution technologies. The approach, published today (December 17) in Nature Methods, could put super-resolution microscopy in the hands of a far greater number of labs, by making it possible to achieve such high-quality images from standard benchtop microscopes, coauthor Aydogan Ozcan of the University of California, Los Angeles tells The Scientist. “[Super-resolution approaches] are really limited to resource-rich environments in terms of both equipment and expertise. Now, through AI, we’re changing the game.”
Over the past year or two, researchers in the field of microscopy have tinkered with AI techniques ...
