BIOMAT Database Logo BIOMAT Database Logo

Classification of red blood cell images using a neural network. 1994

S A Krishna, and J A Orr, and D R Westenskow
Department of Medical Informatics, University of Utah, Salt Lake City.

UI MeSH Term Description Entries
D004912 Erythrocytes Red blood cells. Mature erythrocytes are non-nucleated, biconcave disks containing HEMOGLOBIN whose function is to transport OXYGEN. Blood Cells, Red,Blood Corpuscles, Red,Red Blood Cells,Red Blood Corpuscles,Blood Cell, Red,Blood Corpuscle, Red,Erythrocyte,Red Blood Cell,Red Blood Corpuscle
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D012680 Sensitivity and Specificity Binary classification measures to assess test results. Sensitivity or recall rate is the proportion of true positives. Specificity is the probability of correctly determining the absence of a condition. (From Last, Dictionary of Epidemiology, 2d ed) Specificity,Sensitivity,Specificity and Sensitivity
D016571 Neural Networks, Computer A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming. Computational Neural Networks,Connectionist Models,Models, Neural Network,Neural Network Models,Neural Networks (Computer),Perceptrons,Computational Neural Network,Computer Neural Network,Computer Neural Networks,Connectionist Model,Model, Connectionist,Model, Neural Network,Models, Connectionist,Network Model, Neural,Network Models, Neural,Network, Computational Neural,Network, Computer Neural,Network, Neural (Computer),Networks, Computational Neural,Networks, Computer Neural,Networks, Neural (Computer),Neural Network (Computer),Neural Network Model,Neural Network, Computational,Neural Network, Computer,Neural Networks, Computational,Perceptron

Related Publications

S A Krishna, and J A Orr, and D R Westenskow
Convolutional neural network for cell classification using microscope images of intracellular actin networks.
January 2019, PloS one,
S A Krishna, and J A Orr, and D R Westenskow
A deep convolutional neural network for classification of red blood cells in sickle cell anemia.
October 2017, PLoS computational biology,
S A Krishna, and J A Orr, and D R Westenskow
Laterality Classification of Fundus Images Using Interpretable Deep Neural Network.
December 2018, Journal of digital imaging,
S A Krishna, and J A Orr, and D R Westenskow
Red blood cell phenotyping from 3D confocal images using artificial neural networks.
May 2021, PLoS computational biology,
S A Krishna, and J A Orr, and D R Westenskow
Melanoma Classification on Dermoscopy Images Using a Neural Network Ensemble Model.
March 2017, IEEE transactions on medical imaging,
S A Krishna, and J A Orr, and D R Westenskow
An intelligent neural network model to detect red blood cells for various blood structure classification in microscopic medical images.
February 2024, Heliyon,
S A Krishna, and J A Orr, and D R Westenskow
Classification of Brain Tumours in MRI Images using a Convolutional Neural Network.
March 2023, Current medical imaging,
S A Krishna, and J A Orr, and D R Westenskow
Efficient leukocytes detection and classification in microscopic blood images using convolutional neural network coupled with a dual attention network.
February 2024, Computers in biology and medicine,
S A Krishna, and J A Orr, and D R Westenskow
Cell Classification in ER-Stained Whole Slide Breast Cancer Images Using Convolutional Neural Network.
July 2018, Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference,
S A Krishna, and J A Orr, and D R Westenskow
Melanoma Classification Using a Novel Deep Convolutional Neural Network with Dermoscopic Images.
February 2022, Sensors (Basel, Switzerland),
Copied contents to your clipboard!