AIMC Topic: Cell Size
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Using optimal transport theory to optimize a deep convolutional neural network microscopic cell counting method.
Medical & biological engineering & computing
Aug 3, 2023
Medical image processing has become increasingly important in recent years, particularly in the field of microscopic cell imaging. However, accurately counting the number of cells in an image can be a challenging task due to the significant variation...
Cell morphology-based machine learning models for human cell state classification.
NPJ systems biology and applications
May 26, 2021
Herein, we implement and access machine learning architectures to ascertain models that differentiate healthy from apoptotic cells using exclusively forward (FSC) and side (SSC) scatter flow cytometry information. To generate training data, colorecta...
Detecting cells rotations for increasing the robustness of cell sizing by impedance measurements, with or without machine learning.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
May 7, 2021
The Coulter principle is a widespread technique for sizing red blood cells (RBCs) in hematological analyzers. It is based on the monitoring of the electrical perturbations generated by cells passing through a micro-orifice, in which a concentrated el...
Machine Learning based histology phenotyping to investigate the epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits.
PLoS computational biology
Aug 14, 2020
Genetic studies have recently highlighted the importance of fat distribution, as well as overall adiposity, in the pathogenesis of obesity-associated diseases. Using a large study (n = 1,288) from 4 independent cohorts, we aimed to investigate the re...
An Artificial Neural Network Assisted Dynamic Light Scattering Procedure for Assessing Living Cells Size in Suspension.
Sensors (Basel, Switzerland)
Jun 17, 2020
Dynamic light scattering (DLS) is an essential technique used for assessing the size of the particles in suspension, covering the range from nanometers to microns. Although it has been very well established for quite some time, improvement can still ...
Intelligent image-based deformation-assisted cell sorting with molecular specificity.
Nature methods
May 25, 2020
Although label-free cell sorting is desirable for providing pristine cells for further analysis or use, current approaches lack molecular specificity and speed. Here, we combine real-time fluorescence and deformability cytometry with sorting based on...
CTRL - a label-free artificial intelligence method for dynamic measurement of single-cell volume.
Journal of cell science
Apr 14, 2020
Measuring the physical size of a cell is valuable in understanding cell growth control. Current single-cell volume measurement methods for mammalian cells are labor intensive, inflexible and can cause cell damage. We introduce CTRL: Cell Topography R...
Kernel-Based Microfluidic Constriction Assay for Tumor Sample Identification.
ACS sensors
Jul 18, 2018
A high-throughput multiconstriction microfluidic channels device can distinguish human breast cancer cell lines (MDA-MB-231, HCC-1806, MCF-7) from immortalized breast cells (MCF-10A) with a confidence level of ∼81-85% at a rate of 50-70 cells/min bas...
Segmentation of corneal endothelium images using a U-Net-based convolutional neural network.
Artificial intelligence in medicine
Apr 19, 2018
Diagnostic information regarding the health status of the corneal endothelium may be obtained by analyzing the size and the shape of the endothelial cells in specular microscopy images. Prior to the analysis, the endothelial cells need to be extracte...
Image based Machine Learning for identification of macrophage subsets.
Scientific reports
Jun 14, 2017
Macrophages play a crucial rule in orchestrating immune responses against pathogens and foreign materials. Macrophages have remarkable plasticity in response to environmental cues and are able to acquire a spectrum of activation status, best exemplif...
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