Phase recovery (PR) refers to calculating the phase of the light field from its intensity
measurements. As exemplified from quantitative phase imaging and coherent diffraction …

With the explosive growth of mathematical optimization and computing hardware, deep
neural networks (DNN) have become tremendously powerful tools to solve many …

Deep learning-based image reconstruction methods have achieved remarkable success in
phase recovery and holographic imaging. However, the generalization of their image …

Digital in-line holographic microscopy (DIHM) enables efficient and cost-effective
computational quantitative phase imaging with a large field of view, making it valuable for …

Digital holography is one of the most widely used label-free microscopy techniques in
biomedical imaging. Recovery of the missing phase information on a hologram is an …

Optical microscopy has emerged as a key driver of fundamental research since it provides
the ability to probe into imperceptible structures in the biomedical world. For the detailed …

摘要随着大数据时代的来临, 深度学习被广泛地应用于图像处理, 语音识别, 自动驾驶等领域.
作为一种数据驱动的算法, 深度学习应用于光学领域可以有效地提高计算效率和成像质量 …

The application of deep learning techniques has greatly enhanced holographic imaging
capabilities, leading to improved phase recovery and image reconstruction. Here, we …

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

This review examines the biological physics of intracellular transport probed by the coherent
optics of dynamic light scattering from optically thick living tissues. Cells and their …