Live-cell imaging powered by computation
The proliferation of microscopy methods for live-cell imaging offers many new possibilities
for users but can also be challenging to navigate. The prevailing challenge in live-cell …
for users but can also be challenging to navigate. The prevailing challenge in live-cell …
Physics-informed computer vision: A review and perspectives
The incorporation of physical information in machine learning frameworks is opening and
transforming many application domains. Here the learning process is augmented through …
transforming many application domains. Here the learning process is augmented through …
Field-dependent deep learning enables high-throughput whole-cell 3D super-resolution imaging
Single-molecule localization microscopy in a typical wide-field setup has been widely used
for investigating subcellular structures with super resolution; however, field-dependent …
for investigating subcellular structures with super resolution; however, field-dependent …
DEEP-squared: deep learning powered De-scattering with Excitation Patterning
Limited throughput is a key challenge in in vivo deep tissue imaging using nonlinear optical
microscopy. Point scanning multiphoton microscopy, the current gold standard, is slow …
microscopy. Point scanning multiphoton microscopy, the current gold standard, is slow …
Deep-learning-augmented computational miniature mesoscope
Fluorescence microscopy is essential to study biological structures and dynamics. However,
existing systems suffer from a trade-off between field of view (FOV), resolution, and system …
existing systems suffer from a trade-off between field of view (FOV), resolution, and system …
Coordinate-based neural representations for computational adaptive optics in widefield microscopy
Widefield microscopy is widely used for non-invasive imaging of biological structures at
subcellular resolution. When applied to a complex specimen, its image quality is degraded …
subcellular resolution. When applied to a complex specimen, its image quality is degraded …
INFWIDE: Image and feature space Wiener deconvolution network for non-blind image deblurring in low-light conditions
Under low-light environment, handheld photography suffers from severe camera shake
under long exposure settings. Although existing deblurring algorithms have shown …
under long exposure settings. Although existing deblurring algorithms have shown …
Optofluidic imaging meets deep learning: from merging to emerging
Propelled by the striking advances in optical microscopy and deep learning (DL), the role of
imaging in lab-on-a-chip has dramatically been transformed from a silo inspection tool to a …
imaging in lab-on-a-chip has dramatically been transformed from a silo inspection tool to a …
Spatio-Temporal Turbulence Mitigation: A Translational Perspective
Recovering images distorted by atmospheric turbulence is a challenging inverse problem
due to the stochastic nature of turbulence. Although numerous turbulence mitigation (TM) …
due to the stochastic nature of turbulence. Although numerous turbulence mitigation (TM) …
Different channels to transmit information in scattering media
X Zhang, J Gao, Y Gan, C Song, D Zhang, S Zhuang… - PhotoniX, 2023 - Springer
A communication channel should be built to transmit information from one place to another.
Imaging is 2 or higher dimensional information communication. Conventionally, an imaging …
Imaging is 2 or higher dimensional information communication. Conventionally, an imaging …