Fluorescence microscopy-based image restoration has received widespread attention in the life sciences and has led to significant progress, benefiting from deep learning technology. However, most ...

Super-resolution microscopy, particularly localization-based methods, necessitates careful balancing of optical complexity, computational demands, and user accessibility. Conventional strategies ...

Volumetric fluorescence microscopy is an indispensable tool for comprehensive studies of cells and organs. Since the specimens are inherently three-dimensional (3D), the optimal imaging system should ...

In PhotoniX, researchers report a self-supervised deep learning method that denoises dynamic fluorescence images in vivo without requiring clean training data. The figure shows in vivo venule images ...

In life sciences, confocal fluorescence microscopy (CFM) is widely regarded for producing high-resolution cellular images. However, it requires fluorescent staining, which poses risks of ...

A new two-photon fluorescence microscope developed at UC Davis can capture high-speed images of neural activity at cellular resolution thanks to a new adaptive sampling scheme and line illumination.

In recent years, fluorescence quenching microscopy (FQM) 1-3 has emerged as a viable technique that allows for the swift, cost-effective, and accurate imaging of two-dimensional (2D) materials like ...

FLIM principles. Schematic overview of fluorescence lifetime data acquisition and analysis in time−domain (td) and frequency−domain (fd) modes. In tdFLIM, photon arrival times are recorded after each ...