AIMC Topic: Microscopy

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Artificial intelligence assistance significantly improves Gleason grading of prostate biopsies by pathologists.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc Aug 5, 2020
The Gleason score is the most important prognostic marker for prostate cancer patients, but it suffers from significant observer variability. Artificial intelligence (AI) systems based on deep learning can achieve pathologist-level performance at Gle...
Observer Variation Prostatic Neoplasms Neoplasm Grading Biopsy Pathologists Microscopy Image Interpretation, Computer-Assisted Diagnosis, Computer-Assisted Deep Learning Humans Predictive Value of Tests Reproducibility of Results Male
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High spatially sensitive quantitative phase imaging assisted with deep neural network for classification of human spermatozoa under stressed condition.

Scientific reports Aug 4, 2020
Sperm cell motility and morphology observed under the bright field microscopy are the only criteria for selecting a particular sperm cell during Intracytoplasmic Sperm Injection (ICSI) procedure of Assisted Reproductive Technology (ART). Several fact...
Deep Learning Hydrogen Peroxide Oxidative Stress Humans Male Spermatozoa Microscopy Signal-To-Noise Ratio Image Processing, Computer-Assisted Cryopreservation Ethanol
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Machine learning and statistical analyses for extracting and characterizing "fingerprints" of antibody aggregation at container interfaces from flow microscopy images.

Biotechnology and bioengineering Jul 28, 2020
Therapeutic proteins are exposed to numerous stresses during their manufacture, shipping, storage and administration to patients, causing them to aggregate and form particles through a variety of different mechanisms. These varied mechanisms generate...
Machine Learning Algorithms Image Processing, Computer-Assisted Antibodies Microscopy Protein Stability Immunoglobulins, Intravenous Protein Aggregates
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FecalNet: Automated detection of visible components in human feces using deep learning.

Medical physics Jul 18, 2020
PURPOSE: To automate the detection and identification of visible components in feces for early diagnosis of gastrointestinal diseases, we propose FecalNet, a method using multiple deep neural networks.
Feces Leukocytes Microscopy Humans Neural Networks, Computer Deep Learning
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Image based cellular contractile force evaluation with small-world network inspired CNN: SW-UNet.

Biochemical and biophysical research communications Jul 7, 2020
We propose an image based cellular contractile force evaluation method using a machine learning technique. We use a special substrate that exhibits wrinkles when cells grab the substrate and contract, and the wrinkles can be used to visualize the for...
Mutation Microscopy Proto-Oncogene Proteins p21(ras) Image Processing, Computer-Assisted Osteosarcoma Bone Neoplasms Humans Neural Networks, Computer Machine Learning Algorithms Biomechanical Phenomena Cell Line, Tumor
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Deep learning approach to describe and classify fungi microscopic images.

PloS one Jun 30, 2020
Preliminary diagnosis of fungal infections can rely on microscopic examination. However, in many cases, it does not allow unambiguous identification of the species due to their visual similarity. Therefore, it is usually necessary to use additional b...
Support Vector Machine Deep Learning Fungi Image Processing, Computer-Assisted Microscopy
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CellCountCV-A Web-Application for Accurate Cell Counting and Automated Batch Processing of Microscopic Images Using Fully Convolutional Neural Networks.

Sensors (Basel, Switzerland) Jun 29, 2020
In vitro cellular models are promising tools for studying normal and pathological conditions. One of their important applications is the development of genetically engineered biosensor systems to investigate, in real time, the processes occurring in ...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Cell Count Microscopy Automation
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Utilization of a Deep Learning Algorithm for Microscope-Based Fatty Vacuole Quantification in a Fatty Liver Model in Mice.

Toxicologic pathology Jun 8, 2020
Quantification of fatty vacuoles in the liver, with differentiation from lumina of liver blood vessels and bile ducts, is an example where the traditional semiquantitative pathology assessment can be enhanced with artificial intelligence (AI) algorit...
Animals Deep Learning Mice Artificial Intelligence Machine Learning Algorithms Microscopy Image Interpretation, Computer-Assisted Vacuoles Disease Models, Animal Liver Non-alcoholic Fatty Liver Disease
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Deep Learning Identifies Cardiomyocyte Nuclei With High Precision.

Circulation research Jun 3, 2020
Reproducibility of Results Animals Deep Learning Image Processing, Computer-Assisted Mice Fluorescent Dyes Biomarkers Immunohistochemistry Mice, Transgenic Myosin Heavy Chains Microscopy Myocytes, Cardiac Cell Nucleus Troponin T Integrases Indoles
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Particulate impurities in cell-based medicinal products traced by flow imaging microscopy combined with deep learning for image analysis.

Cytotherapy Jun 2, 2020
Cell-based medicinal products (CBMPs) are rapidly gaining importance in the treatment of life-threatening diseases. However, the analytical toolbox for characterization of CBMPs is limited. The aim of our study was to develop a method based on flow i...
Deep Learning Microscopy Humans Neural Networks, Computer
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