AIMC Topic: Microscopy

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deepBlink: threshold-independent detection and localization of diffraction-limited spots.

Nucleic acids research Jul 21, 2021
Detection of diffraction-limited spots in single-molecule microscopy images is traditionally performed with mathematical operators designed for idealized spots. This process requires manual tuning of parameters that is time-consuming and not always r...
Image Processing, Computer-Assisted Microscopy Neural Networks, Computer Software
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Temporal and spectral unmixing of photoacoustic signals by deep learning.

Optics letters Jun 1, 2021
Improving the imaging speed of multi-parametric photoacoustic microscopy (PAM) is essential to leveraging its impact in biomedicine. However, to avoid temporal overlap, the A-line rate is limited by the acoustic speed in biological tissues to a few m...
Microscopy Photoacoustic Techniques Deep Learning Time Factors
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Digital holographic deep learning of red blood cells for field-portable, rapid COVID-19 screening.

Optics letters May 15, 2021
Rapid screening of red blood cells for active infection of COVID-19 is presented using a compact and field-portable, 3D-printed shearing digital holographic microscope. Video holograms of thin blood smears are recorded, individual red blood cells are...
COVID-19 Reproducibility of Results Humans Deep Learning Microscopy SARS-CoV-2 Sensitivity and Specificity COVID-19 Testing Image Enhancement Erythrocytes Holography
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[Aid of artificial intelligence for the anatomo-pathological diagnosis of tumours].

Revue medicale de Liege May 1, 2021
The anatomo-pathological diagnosis of tumors is based on many criteria related mainly to image analysis. Currently, in most pathology laboratories, tissues or cells are placed on glass slides and directly analyzed with an optical microscope. Because ...
Microscopy Artificial Intelligence Algorithms Neoplasms Image Processing, Computer-Assisted Humans
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Deep-learning-enhanced light-field microscopy.

Nature methods May 1, 2021
Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted Microscopy
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The promise and peril of deep learning in microscopy.

Nature methods Feb 1, 2021
Microscopy Deep Learning Neural Networks, Computer
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Sharper signals: how machine learning is cleaning up microscopy images.

Nature Jan 1, 2021
Humans Microscopy Artifacts Machine Learning Unsupervised Machine Learning
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Deep learning model for the prediction of microsatellite instability in colorectal cancer: a diagnostic study.

The Lancet. Oncology Jan 1, 2021
BACKGROUND: Detecting microsatellite instability (MSI) in colorectal cancer is crucial for clinical decision making, as it identifies patients with differential treatment response and prognosis. Universal MSI testing is recommended, but many patients...
Diagnosis, Computer-Assisted Deep Learning Genetic Predisposition to Disease Staining and Labeling Reproducibility of Results Image Interpretation, Computer-Assisted Colorectal Neoplasms Coloring Agents Eosine Yellowish-(YS) Humans Hematoxylin Predictive Value of Tests Microscopy Phenotype Microsatellite Instability
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Smart solutions for automated imaging.

Nature methods Nov 1, 2020
Microscopy Algorithms Artificial Intelligence Image Interpretation, Computer-Assisted Animals
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BeadNet: deep learning-based bead detection and counting in low-resolution microscopy images.

Bioinformatics (Oxford, England) Nov 1, 2020
MOTIVATION: An automated counting of beads is required for many high-throughput experiments such as studying mimicked bacterial invasion processes. However, state-of-the-art algorithms under- or overestimate the number of beads in low-resolution imag...
Microscopy Deep Learning Image Processing, Computer-Assisted Software Algorithms
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