The competition between resolution and the imaging field of view is a long-standing problem
in traditional imaging systems—they can produce either an image of a small area with fine …

When it comes to “phase measurement” or “quantitative phase imaging”, many people will
automatically connect them with “laser” and “interferometry”. Indeed, conventional …

Quantitative phase imaging (QPI) has emerged as a valuable tool for biomedical research
thanks to its unique capabilities for quantifying optical thickness variation of living cells and …

Image stacks provide invaluable 3D information in various biological and pathological
imaging applications. Fourier ptychographic microscopy (FPM) enables reconstructing high …

Ptychography is a form of phase imaging that uses iterative algorithms to reconstruct an
image of a specimen from a series of diffraction patterns. It is swiftly developing into a …

Holography provides access to the optical phase. The emerging compressive phase
retrieval approach can achieve in-line holographic imaging beyond the information-theoretic …

This paper presents a new algorithm, termed truncated amplitude flow (TAF), to recover an
unknown vector x from a system of quadratic equations of the form yi=|< ai, x>| 2, where ai's …

Traditional imaging systems exhibit a well-known trade-off between the resolution and the
field of view of their captured images. Typical cameras and microscopes can either “zoom in” …

Convolutional neural networks (CNNs) have gained tremendous success in solving complex
inverse problems. The aim of this work is to develop a novel CNN framework to reconstruct …

We introduce a novel deep-learning inspired formulation of the\textit {phase retrieval
problem}, which asks to recover a signal $ y_0\in\R^ n $ from $ m $ quadratic observations …