High-throughput widefield fluorescence imaging of 3D samples using deep learning for 2D projection image restoration.

ABSTRACT: Fluorescence microscopy is a core method for visualizing and quantifying the spatial and temporal dynamics of complex biological processes. While many fluorescent microscopy techniques exist, due to its cost-effectiveness and accessibility, widefield fluorescent imaging remains one of the most widely used. To accomplish imaging of 3D samples, conventional widefield fluorescence imaging entails acquiring a sequence of 2D images spaced along the z-dimension, typically called a z-stack. Oftentimes, the first step in an analysis pipeline is to project that 3D volume into a single 2D image because 3D image data can be cumbersome to manage and challenging to analyze and interpret. Furthermore, z-stack acquisition is often time-consuming, which consequently may induce photodamage to the biologica

SUBMITTER: Forsgren E 

PROVIDER: S-EPMC9119453 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature