BIOMEDICAL IMAGE TEXTURE ANALYSIS SYSTEM
- Authors: Polyakov E.V.1, Dmitrieva V.V.1
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Affiliations:
- National Research Nuclear University MEPhI
- Issue: No 2 (2025)
- Pages: 85-94
- Section: MODELS, SYSTEMS, MECHANISMS IN THE TECHNIQUE
- URL: https://journals.rcsi.science/2227-8486/article/view/307555
- DOI: https://doi.org/10.21685/2227-8486-2025-2-7
- ID: 307555
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Abstract
Background. In today's healthcare environment, there is an increasing need for efficient methods to analyze biomedical images for disease diagnosis. The present study aims to develop a biomedical image texture analysis system that uses various approaches to detect structural differences between objects. Materials and methods. In this work, local pixel distributions, Fourier transform, and fractal analysis methods are applied. A random forest classifier and dimensionality reduction and clustering methods implemented in the Scikit-learn library are used to evaluate the informativeness of texture features. Experimental data include bone marrow cell images, CT scans, and skin neoplasms. Results. Experimental results show that features based on spatial adjacency matrix and Fourier transform are the most informative for classifying blood and bone marrow cell images. For CT images and skin neoplasms, effective texture features are also identified, achieving f1 metrics as high as 0.93. Conclusions. The developed system enables efficient texture analysis of biomedical images and provides tools for automated evaluation of tumor features, which can significantly improve diagnostic accuracy. Further research will focus on extending the functionality of the system and improving data visualization methods.
About the authors
Evgeny V. Polyakov
National Research Nuclear University MEPhI
Author for correspondence.
Email: EVPolyakov@mephi.ru
Candidate of technical sciences, associate professor of the subdepartment of medical physics
(Moscow Engineering Physics Institute) (31 Kashirskoe shosse, Moscow, Russia)Valentina V. Dmitrieva
National Research Nuclear University MEPhI
Email: VVdmitriyeva@mephi.ru
Candidate of technical sciences, associate professor of the sub-department of electrophysical systems
(Moscow Engineering Physics Institute) (31 Kashirskoe shosse, Moscow, Russia)References
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