AIMC Topic: Microscopy, Fluorescence
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Simultaneous detection of trace protein biomarkers from a single drop of blood using AI-enhanced smartphone-based digital microscopy.
Biosensors & bioelectronics
Feb 13, 2025
The detection of early-stage diseases is often impeded by the low concentrations of protein biomarkers, necessitating sophisticated and costly technologies. In response, we have developed an advanced cyber-physical system that integrates blood plasma...
Deep Learning and Single-Molecule Localization Microscopy Reveal Nanoscopic Dynamics of DNA Entanglement Loci.
ACS nano
Feb 4, 2025
Understanding molecular dynamics at the nanoscale remains challenging due to limitations in the temporal resolution of current imaging techniques. Deep learning integrated with Single-Molecule Localization Microscopy (SMLM) offers opportunities to pr...
UNET-FLIM: A Deep Learning-Based Lifetime Determination Method Facilitating Real-Time Monitoring of Rapid Lysosomal pH Variations in Living Cells.
Analytical chemistry
Feb 4, 2025
Lifetime determination plays a crucial role in fluorescence lifetime imaging microscopy (FLIM). We introduce UNET-FLIM, a deep learning architecture based on a one-dimensional U-net, specifically designed for lifetime determination. UNET-FLIM focuses...
Accelerating biopharmaceutical cell line selection with label-free multimodal nonlinear optical microscopy and machine learning.
Communications biology
Feb 3, 2025
The selection of high-performing cell lines is crucial for biopharmaceutical production but is often time-consuming and labor-intensive. We investigated label-free multimodal nonlinear optical microscopy for non-perturbative profiling of biopharmaceu...
A deep learning pipeline for three-dimensional brain-wide mapping of local neuronal ensembles in teravoxel light-sheet microscopy.
Nature methods
Jan 27, 2025
Teravoxel-scale, cellular-resolution images of cleared rodent brains acquired with light-sheet fluorescence microscopy have transformed the way we study the brain. Realizing the potential of this technology requires computational pipelines that gener...
Deep learning-based aberration compensation improves contrast and resolution in fluorescence microscopy.
Nature communications
Jan 2, 2025
Optical aberrations hinder fluorescence microscopy of thick samples, reducing image signal, contrast, and resolution. Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisit...
Deep learning-enabled filter-free fluorescence microscope.
Science advances
Jan 1, 2025
Optical filtering is an indispensable part of fluorescence microscopy for selectively highlighting molecules labeled with a specific fluorophore and suppressing background noise. However, the utilization of optical filtering sets increases the comple...
A Single-Cell Interrogation System from Scratch: Microfluidics and Deep Learning.
The journal of physical chemistry. B
Nov 15, 2024
Live-cell imaging using fluorescence microscopy enables researchers to study cellular processes in unprecedented detail. These techniques are becoming increasingly popular among microbiologists. The emergence of microfluidics and deep learning has si...
Deep learning method for detecting fluorescence spots in cancer diagnostics via fluorescence in situ hybridization.
Scientific reports
Nov 8, 2024
Fluorescence in Situ Hybridization (FISH) is a technique for macromolecule identification that utilizes the complementarity of DNA or DNA/RNA double strands. Probes, crafted from selected DNA strands tagged with fluorophore-coupled nucleotides, hybri...
Deep-Learning-Based Segmentation of Cells and Analysis (DL-SCAN).
Biomolecules
Oct 23, 2024
With the recent surge in the development of highly selective probes, fluorescence microscopy has become one of the most widely used approaches to studying cellular properties and signaling in living cells and tissues. Traditionally, microscopy image ...
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