AI Medical Compendium Topic

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Microscopy, Fluorescence

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Deep Learning Solution for Quantification of Fluorescence Particles on a Membrane.

Sensors (Basel, Switzerland)
The detection and quantification of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus particles in ambient waters using a membrane-based in-gel loop-mediated isothermal amplification (mgLAMP) method can play an important role in larg...

Correlative Fluorescence and Raman Microscopy to Define Mitotic Stages at the Single-Cell Level: Opportunities and Limitations in the AI Era.

Biosensors
Nowadays, morphology and molecular analyses at the single-cell level have a fundamental role in understanding biology better. These methods are utilized for cell phenotyping and in-depth studies of cellular processes, such as mitosis. Fluorescence mi...

Machine learning assisted interferometric structured illumination microscopy for dynamic biological imaging.

Nature communications
Structured Illumination Microscopy, SIM, is one of the most powerful optical imaging methods available to visualize biological environments at subcellular resolution. Its limitations stem from a difficulty of imaging in multiple color channels at onc...

Volumetric imaging of fast cellular dynamics with deep learning enhanced bioluminescence microscopy.

Communications biology
Bioluminescence microscopy is an appealing alternative to fluorescence microscopy, because it does not depend on external illumination, and consequently does neither produce spurious background autofluorescence, nor perturb intrinsically photosensiti...

Incorporating the image formation process into deep learning improves network performance.

Nature methods
We present Richardson-Lucy network (RLN), a fast and lightweight deep learning method for three-dimensional fluorescence microscopy deconvolution. RLN combines the traditional Richardson-Lucy iteration with a fully convolutional network structure, es...

Rationalized deep learning super-resolution microscopy for sustained live imaging of rapid subcellular processes.

Nature biotechnology
The goal when imaging bioprocesses with optical microscopy is to acquire the most spatiotemporal information with the least invasiveness. Deep neural networks have substantially improved optical microscopy, including image super-resolution and restor...

Simple and Robust Deep Learning Approach for Fast Fluorescence Lifetime Imaging.

Sensors (Basel, Switzerland)
Fluorescence lifetime imaging (FLIM) is a powerful tool that provides unique quantitative information for biomedical research. In this study, we propose a multi-layer-perceptron-based mixer (MLP-Mixer) deep learning (DL) algorithm named FLIM-MLP-Mixe...

A mitochondria-targeting nitroreductase fluorescent probe with large Stokes shift and long-wavelength emission for imaging hypoxic status in tumor cells.

Analytica chimica acta
Development of a mitochondria-targeting fluorescent probe with large Stokes shift and long-wavelength emission was benefit for accurate detection of hypoxic status, which was known as a major factor of the tumor physiology and influence important pat...

Gradients of three coastal environments off the South China Sea and their impacts on the dynamics of heterotrophic microbial communities.

The Science of the total environment
Heterotrophic fungus-like marine protists are recognized to contribute significantly to the coastal carbon cycling largely due to their high biomass and ability to decompose recalcitrant organic matter. Yet, little is known about their dynamics at po...

Rapid Quantification of Protein Particles in High-Concentration Antibody Formulations.

Journal of pharmaceutical sciences
Current technologies for monitoring the subvisible particles that may be generated during fill-finish operations for protein formulations are cumbersome. Measurement times are generally too long for real-time analysis, and the high protein concentrat...