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Development of technology for choroidal state assessment based on pre-processing and quantitative analysis of void images from angio-OCT data
N.Yu. Ilyasova 1,2, R.T. Samigullin 1, D.V. Kirsh 1,2, N.S. Demin 1,2

1 Samara National Research University,
Moskovskoye Shosse 34, Samara, 443086, Russia;
2 Image Processing Systems Institute, NRC "Kurchatov Institute",
Molodogvardeyskaya 151, Samara, 443001, Russia

 PDF, 3673 kB

DOI: 10.18287/2412-6179-CO-1661

Pages: 767-774.

Full text of article: Russian language.

Abstract:
This paper presents a technology of selecting regions of interest in retinal angio-OCT images for conducting a quantitative analysis of choroidal parameters for the eye disease detection. The relevance of the research is evident from an important role of the choroid in the eye, which provides nourishment to the retina, thus ensuring its normal functioning. Abnormalities in choroid functioning lead to various eye diseases, including degenerative retinal diseases and glaucoma. We propose a method of choroidal condition assessment based on finding areas of vascular signal absence in the retinal angio-OCT images. A comparative analysis of the applicability of the proposed features for the classification of normality and pathology is carried out. The results of study obtained under different parameters of the algorithm of feature calculation reveal that the developed technology shows promise for designing a classifier. The results presented can be useful for specialists in ophthalmology and help to improve the diagnosis and treatment of eye diseases.

Keywords:
biomedical images, optical coherence tomography images, thresholding, choroid, quantitative features, quantitative analysis.

Citation:
Ilyasova NY, Samigullin RT, Kirsh DV, Demin NS. Development of technology for choroidal state assessment based on pre-processing and quantitative analysis of void images from angio-OCT data. Computer Optics 2025; 49(5): 767-774. DOI: 10.18287/2412-6179-CO-1661.

Acknowledgements:
This work was carried out within the state assignment theme FSSS-2023-006 (Theoretical and experimental part) and within the government project of the NRC “Kurchatov Institute” (Software implementation).

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