Analysis of methods and systems for recognition of ear pathologies on otoscopic images

Authors

  • A. Marchuk Vinnytsia National Technical University

DOI:

https://doi.org/10.31649/1681-7893-2025-49-1-227-234

Keywords:

image recognition, deep learning, object localization, feature extraction, bounding boxes, otoscope, real-time detection, algorithm, filtering, disease, ear, YOLO, OCTO, augmented reality

Abstract

An analysis of methods and tools for the analysis and classification of ear pathologies was conducted, identifying their application features, advantages, and disadvantages. As a result of this work, ways to improve ear pathology recognition systems were determined. For this study, the free software package Image Composite Editor (ICE) 2.0 (Microsoft) was used to generate seamless composite images. The combination of different methods and algorithms for image processing and classification significantly increases the reliability of the results obtained. Further studies to improve the accuracy of disease diagnosis can be aimed at combining different image processing algorithms and machine learning algorithms.

Author Biography

A. Marchuk, Vinnytsia National Technical University

postgraduate

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Published

2025-06-18

How to Cite

[1]
A. Marchuk, “Analysis of methods and systems for recognition of ear pathologies on otoscopic images”, Опт-ел. інф-енерг. техн., vol. 49, no. 1, pp. 227–234, Jun. 2025.

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Section

Biomedical Optical And Electronic Systems And Devices

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