AIMC Topic: Microscopy, Fluorescence
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Deep learning for blind structured illumination microscopy.
Scientific reports
May 21, 2022
Blind-structured illumination microscopy (blind-SIM) enhances the optical resolution without the requirement of nonlinear effects or pre-defined illumination patterns. It is thus advantageous in experimental conditions where toxicity or biological fl...
High-throughput widefield fluorescence imaging of 3D samples using deep learning for 2D projection image restoration.
PloS one
May 19, 2022
Fluorescence microscopy is a core method for visualizing and quantifying the spatial and temporal dynamics of complex biological processes. While many fluorescent microscopy techniques exist, due to its cost-effectiveness and accessibility, widefield...
MultiHeadGAN: A deep learning method for low contrast retinal pigment epithelium cell segmentation with fluorescent flatmount microscopy images.
Computers in biology and medicine
May 10, 2022
BACKGROUND: Retinal pigment epithelium (RPE) aging is an important cause of vision loss. As RPE aging is accompanied by changes in cell morphological features, an accurate segmentation of RPE cells is a prerequisite to such morphology analyses. Due t...
Bayesian machine learning analysis of single-molecule fluorescence colocalization images.
eLife
Mar 23, 2022
Multi-wavelength single-molecule fluorescence colocalization (CoSMoS) methods allow elucidation of complex biochemical reaction mechanisms. However, analysis of CoSMoS data is intrinsically challenging because of low image signal-to-noise ratios, non...
Label2label: training a neural network to selectively restore cellular structures in fluorescence microscopy.
Journal of cell science
Feb 10, 2022
Immunofluorescence microscopy is routinely used to visualise the spatial distribution of proteins that dictates their cellular function. However, unspecific antibody binding often results in high cytosolic background signals, decreasing the image con...
Machine learning classification of trajectories from molecular dynamics simulations of chromosome segregation.
PloS one
Jan 21, 2022
In contrast to the well characterized mitotic machinery in eukaryotes it seems as if there is no universal mechanism organizing chromosome segregation in all bacteria. Apparently, some bacteria even use combinations of different segregation mechanism...
Generative adversarial network enables rapid and robust fluorescence lifetime image analysis in live cells.
Communications biology
Jan 11, 2022
Fluorescence lifetime imaging microscopy (FLIM) is a powerful tool to quantify molecular compositions and study molecular states in complex cellular environment as the lifetime readings are not biased by fluorophore concentration or excitation power....
Automating cell counting in fluorescent microscopy through deep learning with c-ResUnet.
Scientific reports
Nov 25, 2021
Counting cells in fluorescent microscopy is a tedious, time-consuming task that researchers have to accomplish to assess the effects of different experimental conditions on biological structures of interest. Although such objects are generally easy t...
A machine learning approach for single cell interphase cell cycle staging.
Scientific reports
Sep 29, 2021
The cell nucleus is a tightly regulated organelle and its architectural structure is dynamically orchestrated to maintain normal cell function. Indeed, fluctuations in nuclear size and shape are known to occur during the cell cycle and alterations in...
Imaging in focus: An introduction to denoising bioimages in the era of deep learning.
The international journal of biochemistry & cell biology
Sep 20, 2021
Fluorescence microscopy enables the direct observation of previously hidden dynamic processes of life, allowing profound insights into mechanisms of health and disease. However, imaging of live samples is fundamentally limited by the toxicity of the ...
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