利用描述性图像代数和布尔代数方法实现眼病诊断自动化

IF 0.7 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS PATTERN RECOGNITION AND IMAGE ANALYSIS Pub Date : 2024-07-04 DOI:10.1134/s1054661824700093
I. B. Gurevich, V. V. Yashina
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引用次数: 0

摘要

摘要 本文介绍了一个用描述性图像代数语言编写的代数模型,用于解决眼科诊断自动化问题。描述性图像代数是一种初步的数学语言,用于在从图像中提取信息时,将处理图像模型和转换图像模型的表示和程序正规化和标准化。为了构建解决眼科诊断自动化问题的代数模型,主要使用单环图像描述性代数。该类代数属于通用线性代数的一类,具有一个具有同一性的σ关联环。使用描述性布尔代数描述了代数模型的一系列转换和步骤。描述性图像代数是描述性图像分析数学装置的主要部分,它是一套逻辑上有条理的描述性方法和模型,用于图像分析和评估。文章定义了描述性图像代数的专门版本,包括一个环和描述性图像布尔代数、图像模型和图像表示,以及构建代数模型所需的图像模型和图像本身的转换。文章介绍了写作过程中使用的图像模型(表示法、形式化描述)。举例说明了使用代数模型解决眼科应用问题的描述性算法方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Automation of Eye Disease Diagnoses Using Descriptive Image Algebras and Boolean Algebra Methods

Abstract

The article presents an algebraic model for solving the problem of automation of ophthalmological diagnostics written in the language of descriptive image algebras. Descriptive image algebras are an initial mathematical language for formalizing and standardizing representations and procedures for processing image models and conversions over them when extracting information from images. To construct an algebraic model for solving the problem of automation of ophthalmological diagnostics, descriptive algebras of images with one ring are mainly used. This class of algebras belongs to the class of universal linear algebras with a sigma-associative ring with identity. A series of conversions and steps of the algebraic model are described using descriptive Boolean algebras over images. Descriptive image algebras are the main section of the mathematical apparatus of descriptive image analysis, which is a logically organized set of descriptive methods and models designed for image analysis and evaluation. The article defines specialized versions of descriptive image algebras with one ring and descriptive Boolean algebras over images, over models and representations of images, and over conversions of image models and images themselves, necessary for constructing an algebraic model. The image models (representations, formalized descriptions) used in writing the article are described. An example of a descriptive algorithmic scheme for solving an applied ophthalmological problem using an algebraic model is constructed.

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来源期刊
PATTERN RECOGNITION AND IMAGE ANALYSIS
PATTERN RECOGNITION AND IMAGE ANALYSIS Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
1.80
自引率
20.00%
发文量
80
期刊介绍: The purpose of the journal is to publish high-quality peer-reviewed scientific and technical materials that present the results of fundamental and applied scientific research in the field of image processing, recognition, analysis and understanding, pattern recognition, artificial intelligence, and related fields of theoretical and applied computer science and applied mathematics. The policy of the journal provides for the rapid publication of original scientific articles, analytical reviews, articles of the world''s leading scientists and specialists on the subject of the journal solicited by the editorial board, special thematic issues, proceedings of the world''s leading scientific conferences and seminars, as well as short reports containing new results of fundamental and applied research in the field of mathematical theory and methodology of image analysis, mathematical theory and methodology of image recognition, and mathematical foundations and methodology of artificial intelligence. The journal also publishes articles on the use of the apparatus and methods of the mathematical theory of image analysis and the mathematical theory of image recognition for the development of new information technologies and their supporting software and algorithmic complexes and systems for solving complex and particularly important applied problems. The main scientific areas are the mathematical theory of image analysis and the mathematical theory of pattern recognition. The journal also embraces the problems of analyzing and evaluating poorly formalized, poorly structured, incomplete, contradictory and noisy information, including artificial intelligence, bioinformatics, medical informatics, data mining, big data analysis, machine vision, data representation and modeling, data and knowledge extraction from images, machine learning, forecasting, machine graphics, databases, knowledge bases, medical and technical diagnostics, neural networks, specialized software, specialized computational architectures for information analysis and evaluation, linguistic, psychological, psychophysical, and physiological aspects of image analysis and pattern recognition, applied problems, and related problems. Articles can be submitted either in English or Russian. The English language is preferable. Pattern Recognition and Image Analysis is a hybrid journal that publishes mostly subscription articles that are free of charge for the authors, but also accepts Open Access articles with article processing charges. The journal is one of the top 10 global periodicals on image analysis and pattern recognition and is the only publication on this topic in the Russian Federation, Central and Eastern Europe.
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