Deep learning-enhanced microscopy with extended depth-of-field
Abstract
A computational imaging platform utilizing a physics-incorporated, deep-learned design of binary phase filter and a jointly optimized deconvolution neural network has been reported, achieving high-resolution, high-contrast imaging over extended depth ranges without the need for serial refocusing.
Yide Zhang
NIH K99 Postdoctoral Fellow
My research is interdisciplinary and focused on developing new types of optical imaging techniques that could advance the work of other researchers and medical personnel in a wide variety of fields. Currently, I am developing next-generation photoacoustic and ultrafast imaging techniques that can observe biological and physical phenomena that are too fast to be imaged with existing methods. The observation of the ultrafast phenomena could provide a better understanding of the fundamentals of life and physical sciences. I am also developing novel quantum imaging approaches that can investigate biological organisms with an imaging performance that cannot be achieved using classical optical imaging. In my free time, I enjoy cooking, hiking, cycling, and traveling.