How deep learning AI will help hologram technology find practical applications

In two new studies, researchers at UCLA used artificial neural networks to reconstruct a hologram -- not just any hologram, though. Not only is the technique an advancement of holographic technology, but the resulting microscopic images could have fascinating medical applications. In the first study, published in the journal, Light: Science & Applications, researchers used deep learning to create images of biological samples like blood, Pap smears, and other thin tissue samples. The neural network technique proved to be easier and faster than the usual methods used to make holograms, which often require an abundance of physical measurements and computational input. In the second study, the team applied their deep learning framework to improve the resolution and quality of the microscopic images, which could help doctors detect very small abnormalities in a large blood or tissue sample.