AIMC Topic: Cell Count

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Equivalent circuit models for a biomembrane impedance sensor and analysis of electrochemical impedance spectra based on support vector regression.

Medical & biological engineering & computing Apr 2, 2019
In this study, an electrochemical impedance biosensor was developed as a simple and fast method for real-time monitoring of biofilm binding properties via continuous impedance spectroscopy. To prepare the sensing membrane, cells were immobilized onto...
Principal Component Analysis Cell Count Electrodes Support Vector Machine MCF-7 Cells Dielectric Spectroscopy Cells, Immobilized Humans Collodion Electric Impedance Membranes, Artificial Biosensing Techniques
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Automated segmentation of the corneal endothelium in a large set of 'real-world' specular microscopy images using the U-Net architecture.

Scientific reports Mar 18, 2019
Monitoring the density of corneal endothelial cells (CEC) is essential in the management of corneal diseases. Its manual calculation is time consuming and prone to errors. U-Net, a neural network for biomedical image segmentation, has shown promising...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Endothelial Cells Endothelium, Corneal Cell Count Microscopy
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Light-driven ultrasensitive self-powered cytosensing of circulating tumor cells via integration of biofuel cells and a photoelectrochemical strategy.

Journal of materials chemistry. B Mar 8, 2019
Herein, a light-driven, membrane-less and mediator-less self-powered cytosensing platform via integration of biofuel cells (BFCs) and a photoelectrochemical strategy was developed for ultrasensitive detection of circulating tumor cells (CTCs). To con...
HeLa Cells Humans Bioelectric Energy Sources Neoplastic Cells, Circulating Electrochemical Techniques Biosensing Techniques Cell Count
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Automatic ground truth for deep learning stereology of immunostained neurons and microglia in mouse neocortex.

Journal of chemical neuroanatomy Mar 2, 2019
Collection of unbiased stereology data currently relies on relatively simple, low throughput technology developed in the mid-1990s. In an effort to improve the accuracy and efficiency of these integrated hardware-software-digital microscopy systems, ...
Animals Neurons Mice Deep Learning Microglia Histological Techniques Image Processing, Computer-Assisted Cell Count Neocortex
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Automated Cell Counts on Tissue Sections by Deep Learning and Unbiased Stereology.

Journal of chemical neuroanatomy Dec 27, 2018
In recent decades stereology-based studies have played a significant role in understanding brain aging and developing novel drug discovery strategies for treatment of neurological disease and mental illness. A major obstacle to further progress in a ...
Image Processing, Computer-Assisted Animals Mice Cell Count Deep Learning Brain Imaging, Three-Dimensional
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Estimation of somatic cell count levels of hard cheeses using physicochemical composition and artificial neural networks.

Journal of dairy science Dec 24, 2018
This study addresses the prediction of the somatic cell counts of the milk used in the production of sheep cheese using artificial neural networks. To achieve this objective, the neural network was designed using 33 parameters of the physicochemical ...
Food Handling Cheese Sheep Milk Chemical Phenomena Cell Count Fatty Acids Neural Networks, Computer Animals
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Case study: Evaluating quarter and composite milk sampling for detection of subclinical intramammary infections in dairy cattle.

Preventive veterinary medicine Dec 23, 2018
Our objective was to evaluate a 200,000 cells/mL somatic cell count (SCC) cut-point on both the quarter and composite level to determine its effectiveness at identifying subclinical mastitis infections in one commercial dairy herd in Central New York...
Mastitis, Bovine Asymptomatic Infections Cell Count Dairying Animals Female Milk Cattle
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U-Net: deep learning for cell counting, detection, and morphometry.

Nature methods Dec 17, 2018
U-Net is a generic deep-learning solution for frequently occurring quantification tasks such as cell detection and shape measurements in biomedical image data. We present an ImageJ plugin that enables non-machine-learning experts to analyze their dat...
Cloud Computing Software Design Deep Learning Cell Count Neural Networks, Computer
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Comparison of physical and behavioral traits between dairy cows with low and high somatic cell count.

Preventive veterinary medicine Dec 14, 2018
The objective of this study was to examine associations of locomotion score, hygiene, body condition score (BCS), lying behavior, and milk production with dairy cow somatic cell count (SCC; low or high). Cows from 14 commercial free-stall dairy herds...
Behavior, Animal Locomotion Milk Dairying Animals Cattle Female Cell Count Cross-Sectional Studies
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Quantifying cell densities and biovolumes of phytoplankton communities and functional groups using scanning flow cytometry, machine learning and unsupervised clustering.

PloS one May 10, 2018
Scanning flow cytometry (SFCM) is characterized by the measurement of time-resolved pulses of fluorescence and scattering, enabling the high-throughput quantification of phytoplankton morphology and pigmentation. Quantifying variation at the single c...
Algorithms Ecosystem Flow Cytometry Cell Count Cluster Analysis Machine Learning Phytoplankton
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