Recent years have witnessed the unprecedented progress of deep learning applications in
digital holography (DH). Nevertheless, there remain huge potentials in how deep learning …

摘要近年来, 深度学习技术的爆发式发展引领了机器学习的又一次浪潮. 深度神经网络具备抽象
特征的高效识别与提取能力, 强大的非线性拟合能力, 抗干扰鲁棒性及非凡的泛化能力 …

The conventional reconstruction method of off-axis digital holographic microscopy (DHM)
relies on computational processing that involves spatial filtering of the sample spectrum and …

Existing methods to eliminate the laser speckle noise in quantitative phase imaging always
suffer from the loss of detailed phase information and the resolution reduction in the …

In this paper, a novel approach using deep learning-assisted wavefront correction in beam
rotation holographic tomography to acquire three-dimensional images of native biological …

The digital holographic technique is an interferometric method that provides comprehensive
information on morphological traits such as cell layer thickness and shape as well as access …

Zero-order image is the main source of noise in the hologram acquisition process. In this
paper, a preprocessing method based on deep learning are proposed. Generative …

Digital holographic microscopy as a non‐contacting, non‐invasive, and highly accurate
measurement technology, is becoming a valuable method for quantitatively investigating …

Multispectral quantitative phase imaging (MS-QPI) is a high-contrast label-free technique for
morphological imaging of the specimens. The aim of the present study is to extract spectral …

Adaptive optics (AO) has great applications in many fields and has attracted wide attention
from researchers. However, both traditional and deep learning-based AO methods have …