Objective quality assessment of digital retinal images in screening study
https://doi.org/10.21122/2309-4923-2025-3-47-58
Abstract
The paper presents a new method for automated no-reference quantitative assessment of the quality of digital retinal images for diabetic retinopathy screening. The proposed method does not require localization of anatomical structures and is based on the analysis of the central fragment of the image in the green spectral channel using the Weibull distribution scale parameter for integrating local quality estimates. A comparative analysis of 36 no-reference functions was carried out, two evaluation measures that showed the best results were selected. It was experimentally shown that using a central fragment 50–67% of the original image size allows increasing the accuracy of image quality assessment by 40 % compared to full-image analysis. Scaling this fragment to 512×512 pixels reduces the image analysis time by up to 20 times without losing accuracy. The effectiveness of the method was confirmed on three thousand images from various sources: Kaggle and DDR databases, Belarusian clinical data. The developed approach does not require reference data and can be integrated into mass screening systems of fundus images, reducing the workload of specialists and increasing the availability of diagnostics for patients with limited computing resources.
About the Authors
Yu. I. Golub
United Institute of Informatics Problems, National Academy of Sciences of Belarus
Belarus
Belarus
Yuliya I. Golub –
PhD, Associate Professor, Leading Researcher.
Minsk
V. Starovoitov
United Institute of Informatics Problems, National Academy of Sciences of Belarus
Belarus
Belarus
Valery Starovoitov –
Doctor of Science, Professor.
Minsk
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Review
For citations:
Golub Yu.I., Starovoitov V. Objective quality assessment of digital retinal images in screening study. «System analysis and applied information science». 2025;(3):47-58. (In Russ.) https://doi.org/10.21122/2309-4923-2025-3-47-58
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