Algorithms and methods of image classification for automated medical systems

Modern medicine in the diagnosis of diseases increasingly relies on the use of automated image recognition systems. Automation is of particular importance in the diagnosis of socially significant diseases, when the quality and speed of diagnosis is important. The pathology processes imposes certain...

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Bibliographic Details
Published in:IOP conference series. Materials Science and Engineering 2020-05, Vol.862 (5), p.52067
Main Authors: Kovalev, I V, Shelomentseva, I G, Yakasova, N V, Voroshilova, A A
Format: Article
Language:English
Subjects:
Algorithms
Artificial neural networks
Automation
Criteria
Diagnostic systems
Fuzzy logic
Fuzzy systems
Image classification
Image quality
Medical imaging
Neural networks
Object recognition
Self organizing maps
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Summary:Modern medicine in the diagnosis of diseases increasingly relies on the use of automated image recognition systems. Automation is of particular importance in the diagnosis of socially significant diseases, when the quality and speed of diagnosis is important. The pathology processes imposes certain restrictions on the methods used, which are associated both with image quality and with the speed of analysis. The article discusses the algorithms and methods for classifying medical images as the basis for automated diagnostic systems; Criteria for choosing among them those methods that satisfy the requirements of the task are determined. Based on a comparison of compliance with the criteria of the methods, neural network methods were selected: a neuro-fuzzy network, a convolutional neural network, and self-organizing maps.
ISSN:1757-8981
1757-899X
DOI:10.1088/1757-899X/862/5/052067