Deep Learning Boosts Microscope's Speed

A representation of a neural network provides a backdrop to a fish larva's beating heart. The advent of deep learning, a powerful form of machine learning, has led to rapid advancements in areas such as speech recognition, visual object recognition, genomics and drug discovery. These methods are characterized by multiple processing layers that can tease out intricate patterns and structures in very large, complex data sets. Now, a team of European researchers has incorporated deep learning algorithms into a light-field microscope to enhance both its reconstruction speed and image quality (Nat. Methods, doi: 10.1038/s41592-021-01136-0). The results significantly extend the capabilities of light-field microscopy for whole-brain or whole-animal imaging of living specimens for biomedical research.