Artificial intelligence-enabled quantitative phase imaging methods for life sciences
Quantitative phase imaging, integrated with artificial intelligence, allows for the rapid and
label-free investigation of the physiology and pathology of biological systems. This review …
label-free investigation of the physiology and pathology of biological systems. This review …
Superresolution structured illumination microscopy reconstruction algorithms: a review
X Chen, S Zhong, Y Hou, R Cao, W Wang… - Light: Science & …, 2023 - nature.com
Structured illumination microscopy (SIM) has become the standard for next-generation wide-
field microscopy, offering ultrahigh imaging speed, superresolution, a large field-of-view …
field microscopy, offering ultrahigh imaging speed, superresolution, a large field-of-view …
Transport of intensity diffraction tomography with non-interferometric synthetic aperture for three-dimensional label-free microscopy
We present a new label-free three-dimensional (3D) microscopy technique, termed transport
of intensity diffraction tomography with non-interferometric synthetic aperture (TIDT-NSA) …
of intensity diffraction tomography with non-interferometric synthetic aperture (TIDT-NSA) …
Concept, implementations and applications of Fourier ptychography
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 …
in traditional imaging systems—they can produce either an image of a small area with fine …
[HTML][HTML] Transport of intensity equation: a tutorial
When it comes to “phase measurement” or “quantitative phase imaging”, many people will
automatically connect them with “laser” and “interferometry”. Indeed, conventional …
automatically connect them with “laser” and “interferometry”. Indeed, conventional …
[HTML][HTML] An integrated imaging sensor for aberration-corrected 3D photography
Planar digital image sensors facilitate broad applications in a wide range of areas,,,–, and
the number of pixels has scaled up rapidly in recent years,. However, the practical …
the number of pixels has scaled up rapidly in recent years,. However, the practical …
On the use of deep learning for computational imaging
Since their inception in the 1930–1960s, the research disciplines of computational imaging
and machine learning have followed parallel tracks and, during the last two decades …
and machine learning have followed parallel tracks and, during the last two decades …
On the use of deep learning for phase recovery
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 …
measurements. As exemplified from quantitative phase imaging and coherent diffraction …
Phase recovery and holographic image reconstruction using deep learning in neural networks
Phase recovery from intensity-only measurements forms the heart of coherent imaging
techniques and holography. In this study, we demonstrate that a neural network can learn to …
techniques and holography. In this study, we demonstrate that a neural network can learn to …
Lens-free on-chip 3D microscopy based on wavelength-scanning Fourier ptychographic diffraction tomography
Lens-free on-chip microscopy is a powerful and promising high-throughput computational
microscopy technique due to its unique advantage of creating high-resolution images across …
microscopy technique due to its unique advantage of creating high-resolution images across …