Video-Rate Quantitative Phase Imaging Using a Digital Holographic Microscope and a Generative Adversarial Network.

ABSTRACT: The conventional reconstruction method of off-axis digital holographic microscopy (DHM) relies on computational processing that involves spatial filtering of the sample spectrum and tilt compensation between the interfering waves to accurately reconstruct the phase of a biological sample. Additional computational procedures such as numerical focusing may be needed to reconstruct free-of-distortion quantitative phase images based on the optical configuration of the DHM system. Regardless of the implementation, any DHM computational processing leads to long processing times, hampering the use of DHM for video-rate renderings of dynamic biological processes. In this study, we report on a conditional generative adversarial network (cGAN) for robust and fast quantitative phase imaging in DHM. T

SUBMITTER: Castaneda R 

PROVIDER: S-EPMC8659916 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature