LA JOLLA--(March 8, 2021) Deep learning is a potential tool for scientists to glean more detail from low-resolution images in microscopy, but it's often difficult to gather enough baseline data to train computers in the process. Now, a new method developed by scientists at the Salk Institute could make the technology more accessible--by taking high-resolution images, and artificially degrading them. The new tool, which the researchers call a "crappifier," could make it significantly easier for scientists to get detailed images of cells or cellular structures that have previously been difficult to observe because they require low-light conditions, such as mitochondria, which can divide when stressed by the lasers used to illuminate them. It could also help democratize microscopy, allowing scientists to capture high-resolution images even if they don't have access to powerful microscopes. The findings were published March 8, 2021, in the journal Nature Methods.

The new tool, which the researchers call a "crappifier," could make it significantly easier for scientists to get detailed images of cells or cellular structures that have previously been difficult to observe because they require low-light conditions, such as mitochondria, which can divide when stressed by the lasers used to illuminate them. It could also help democratize microscopy, allowing scientists to capture high-resolution images even if they don't have access to powerful microscopes. The findings were published March 8, 2021, in the journal Nature Methods. "We invest millions of dollars in these microscopes, and we're still struggling to push the limits of what they can do," says Uri Manor, director of the Waitt Advanced Biophotonics Core Facility at Salk. "That's the problem we were trying to solve with deep learning." Deep learning is a type of artificial intelligence (AI) in which computer algorithms learn and improve by studying examples.