https://www.sciencedaily.com/releases/2020/06/200629150539.htm

To loosen this major bottleneck, a team led by MBL Fellow Hari Shroff has devised deep-learning and other computational approaches that dramatically reduce image-analysis time by orders of magnitude -- in some cases, matching the speed of data acquisition itself. They report their results this week in Nature Biotechnology.

"It's like drinking from a firehose without being able to digest what you're drinking," says Shroff of the common problem of having too much imaging data and not enough post-processing power. The team's improvements, which stem from an ongoing collaboration at the Marine Biological Laboratory (MBL), speed up image analysis in three major ways.