A deep-learning-based workflow to deal with the defocusing problem in high-throughput experiments.

ABSTRACT: The increasing throughput of experiments in biomaterials research makes automatic techniques more and more necessary. Among all the characterization methods, microscopy makes fundamental contributions to biomaterials science where precisely focused images are the basis of related research. Although automatic focusing has been widely applied in all kinds of microscopes, defocused images can still be acquired now and then due to factors including background noises of materials and mechanical errors. Herein, we present a deep-learning-based method for the automatic sorting and reconstruction of defocused cell images. First, the defocusing problem is illustrated on a high-throughput cell microarray. Then, a comprehensive dataset of phase-contrast images captured from varied conditions containi

SUBMITTER: Xue Y 

PROVIDER: S-EPMC8665348 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature