AIMC Topic: Microscopy

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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 Protein Stability Image Processing, Computer-Assisted Antibodies Immunoglobulins, Intravenous Microscopy 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...
Deep Learning Support Vector Machine Image Processing, Computer-Assisted Fungi 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 Cell Count Neural Networks, Computer Microscopy Image Processing, Computer-Assisted 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...
Microscopy Image Interpretation, Computer-Assisted Vacuoles Disease Models, Animal Liver Non-alcoholic Fatty Liver Disease Animals Deep Learning Mice Artificial Intelligence Machine Learning Algorithms
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Deep Learning Identifies Cardiomyocyte Nuclei With High Precision.

Circulation research Jun 3, 2020
Indoles Microscopy Myocytes, Cardiac Fluorescent Dyes Troponin T Integrases Myosin Heavy Chains Cell Nucleus Immunohistochemistry Mice, Transgenic Biomarkers Reproducibility of Results Animals Deep Learning Image Processing, Computer-Assisted Mice
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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...
Humans Neural Networks, Computer Deep Learning Microscopy
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An innovative method for screening and evaluating the degree of diabetic retinopathy and drug treatment based on artificial intelligence algorithms.

Pharmacological research Jun 2, 2020
Current methods of evaluating the degree of diabetic retinopathy are highly subjective and have no quantitative standard. To objectively evaluate the slight changes in tissue structure during the early stage of retinal diseases, a subjective interpre...
Retinal Ganglion Cells Pattern Recognition, Automated Retinal Vessels Microscopy Image Interpretation, Computer-Assisted Early Diagnosis Diabetic Retinopathy Animals Diabetes Mellitus, Type 1 Diabetes Mellitus, Type 2 Male Hypoglycemic Agents Drugs, Chinese Herbal Mice Severity of Illness Index Diabetes Mellitus, Experimental Predictive Value of Tests Deep Learning Rats, Wistar Retina
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Detection of Intestinal Protozoa in Trichrome-Stained Stool Specimens by Use of a Deep Convolutional Neural Network.

Journal of clinical microbiology May 26, 2020
Intestinal protozoa are responsible for relatively few infections in the developed world, but the testing volume is disproportionately high. Manual light microscopy of stool remains the gold standard but can be insensitive, time-consuming, and diffic...
Humans Reproducibility of Results Neural Networks, Computer Feces Artificial Intelligence Microscopy
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