AIMC Topic: Microscopy, Fluorescence

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Scan-less machine-learning-enabled incoherent microscopy for minimally-invasive deep-brain imaging.

Optics express Jan 17, 2022
Deep-brain microscopy is strongly limited by the size of the imaging probe, both in terms of achievable resolution and potential trauma due to surgery. Here, we show that a segment of an ultra-thin multi-mode fiber (cannula) can replace the bulky mic...
Animals Image Processing, Computer-Assisted Mice Cells, Cultured Brain Neuroimaging Green Fluorescent Proteins Caenorhabditis elegans Minimally Invasive Surgical Procedures Microscopy, Fluorescence Neurons Neural Networks, Computer Machine Learning
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Convolutional Neural Networks for Classifying Chromatin Morphology in Live-Cell Imaging.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2022
Chromatin is highly structured, and changes in its organization are essential in many cellular processes, including cell division. Recently, advances in machine learning have enabled researchers to automatically classify chromatin morphology in fluor...
Neural Networks, Computer Machine Learning Microscopy, Fluorescence Chromatin
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Fluorescence microscopy datasets for training deep neural networks.

GigaScience May 5, 2021
BACKGROUND: Fluorescence microscopy is an important technique in many areas of biological research. Two factors that limit the usefulness and performance of fluorescence microscopy are photobleaching of fluorescent probes during imaging and, when ima...
Neural Networks, Computer Fluorescent Dyes Machine Learning Microscopy, Fluorescence Image Processing, Computer-Assisted Signal-To-Noise Ratio
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Deep learning for in vivo near-infrared imaging.

Proceedings of the National Academy of Sciences of the United States of America Jan 5, 2021
Detecting fluorescence in the second near-infrared window (NIR-II) up to ∼1,700 nm has emerged as a novel in vivo imaging modality with high spatial and temporal resolution through millimeter tissue depths. Imaging in the NIR-IIb window (1,500-1,700 ...
Fluorescent Dyes Microscopy, Fluorescence Indoles Mice, Nude Mice, Inbred BALB C Intravital Microscopy Cetuximab Indocyanine Green Molecular Imaging Signal-To-Noise Ratio Neoplasms Spectroscopy, Near-Infrared Deep Learning Cell Line, Tumor Mice Lymph Nodes Humans Neural Networks, Computer Animals
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Deep-learning method for data association in particle tracking.

Bioinformatics (Oxford, England) Dec 8, 2020
MOTIVATION: Biological studies of dynamic processes in living cells often require accurate particle tracking as a first step toward quantitative analysis. Although many particle tracking methods have been developed for this purpose, they are typicall...
Deep Learning Microscopy, Fluorescence Humans Neural Networks, Computer Software Algorithms
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3D computational cannula fluorescence microscopy enabled by artificial neural networks.

Optics express Oct 26, 2020
Computational cannula microscopy (CCM) is a high-resolution widefield fluorescence imaging approach deep inside tissue, which is minimally invasive. Rather than using conventional lenses, a surgical cannula acts as a lightpipe for both excitation and...
Animals Imaging, Three-Dimensional Mice Catheters, Indwelling Phantoms, Imaging Equipment Design Cannula Microscopy, Fluorescence Neuroimaging Neural Networks, Computer Neurons Image Enhancement Cells, Cultured Hippocampus Microspheres
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OrgaNet: A Robust Network for Subcellular Organelles Classification in Fluorescence Microscopy Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Automatic identification of subcellular compartments of proteins in fluorescence microscopy images is an important task to quantitatively evaluate cellular processes. A common problem for the development of deep learning based classifiers is that the...
Humans Neural Networks, Computer Organelles Algorithms Microscopy, Fluorescence HeLa Cells
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Combining Deep Learning with Handcrafted Features for Cell Nuclei Segmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Segmentation of cell nuclei in fluorescence microscopy images provides valuable information about the shape and size of the nuclei, its chromatin texture and DNA content. It has many applications such as cell tracking, counting and classification. In...
Chromatin Microscopy, Fluorescence Cell Nucleus Algorithms Deep Learning
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Computational cannula microscopy of neurons using neural networks.

Optics letters Apr 1, 2020
Computational cannula microscopy is a minimally invasive imaging technique that can enable high-resolution imaging deep inside tissue. Here, we apply artificial neural networks to enable real-time, power-efficient image reconstructions that are more ...
Microscopy, Fluorescence Neurons Image Processing, Computer-Assisted Neural Networks, Computer Signal-To-Noise Ratio Rats Rats, Sprague-Dawley Animals
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3D high resolution generative deep-learning network for fluorescence microscopy imaging.

Optics letters Apr 1, 2020
Microscopic fluorescence imaging serves as a basic tool in many research areas including biology, medicine, and chemistry. With the help of optical clearing, large volume imaging of a mouse brain and even a whole body has been enabled. However, const...
Signal-To-Noise Ratio Deep Learning Microscopy, Fluorescence Imaging, Three-Dimensional Neurons
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