Project: №AP19675574. Development of an intelligent system for diagnosing structural changes in pathologies based on the analysis and processing of biomedical images

The project manager is PhD, Professor Mamyrbayev Orken Zhumazhanovich

Key members of the study group:

junior researcher, Momynzhanova K.R.

junior researcher, Zhumagulova Sh.P.

junior researcher, Aitkazina A.А.

Software Engineer  Zhanegizov А.S.

The aim of this work is to increase the reliability of biomedical image analysis by developing a method for processing retinal tomograms, which is used in the system for diagnosing idiopathic macular holes.

To analyze well-known modern optoelectronic systems, methods, and tools for the analysis and processing of biomedical images of the eye fundus; To evaluate the effectiveness of spatial and frequency methods for processing biomedical images of the eye fundus; To improve the method of processing retinal tomograms; To create a model of operations for processing biomedical tomographic images; To develop mathematical models for the analysis of biomedical information based on fuzzy sets in the context of system development; To create a structural model of the system for analyzing structural configurations in idiopathic macular holes (IMH); To develop a fuzzy processing and output module for biomedical information; To design a system for analyzing structural changes in the diagnosis of IMH and to carry out its validation in the field of practical medicine.

The main results of the project’s research and technical activities are presented in the following publications:

Publications indexed in the Web of Science and/or Scopus databases:

1. Mamyrbayev, O., Pavlov, S., Karas, O., Saldan, Y., Momynzhanova, K., & Zhumagulova, S. (2024). Increasing the reliability of diagnosis of diabetic retinopathy based on machine learning. Eastern-European Journal of Enterprise Technologies, 2(9 (128), 17–26. https://doi.org/10.15587/1729-4061.2024.297849
2. Razia J., Min D., Javed R., Mamyrbayev O., Zhumagulova Sh., Momynzhanova K. (2024). High Accuracy Microcalcifications Detection of Breast Cancer Using Wiener Lti Tophat Model. IEEE Access, VOL. 4, pp 1-14, DOI 10.1109/access.2024.3439397
3. Mamyrbayev, O.; Pavlov, S.; Saldan, Y.; Momynzhanova, K.; Zhumagulova, S. Optical and Electronic Expert System for Diagnosing Eye Pathology in Glaucoma. Appl. Sci. 2024, 14, 7816., Q1 (процентиль 76). DOI:     10.3390/app14177816. https://doi.org/10.3390/app14177816
4. Mamyrbayev, O., Pavlov, S., Poplavskyi, O., Momynzhanova, K., Saldan, Y., Zhanegiz, A., Zhumagulova, S. and Zhumazhan, N. 2025. Hybrid Neural Architectures Combining Convolutional and Recurrent Networks for the Early Detection of Retinal Pathologies. Engineering, Technology & Applied Science Research. 15, 4 (Aug. 2025), 25150–25157. DOI:https://doi.org/10.48084/etasr.11521.

Publications recommended by CCES of RK:

1. Мамырбаев О.Ж., Павлов С.В., Момынжанова К.Р. Глаукоманы ерте диагностикалау үшін бұлыңғыр логикаға негізделген сараптамалық жүйе құру. Қазақстан-британ техникалық университетінің хабаршысы, № 3(70) 2024, https://doi.org/10.55452/1998-6688-2024-21-3-37-47
2. Момынжанова, К., Павлов, С., Жумагулова, Ш., & Тунгушбаев, М. (2025). Математические модели и практическая реализация оптико-электронной экспертной системы для выявления глаукомы.Известия НАН РК. Серия физико-математическая, (1), 202–217. DOI: 10.32014/2025.2518-1726.334// https://doi.org/10.32014/2025.2518-1726.334

Proceedings of international conferences:

1. Mamyrbayev, O., Wójcik, W., Pavlov, S., Karas, O., Saldan, Y., Momynzhanova, K., Shvarts, I., Baranovska, I., Rakhmetulina, S., & Amirgaliyev, B. (2023). Optical method of investigating eye diseases and system for diagnosing diabetic retinopathy. Proceedings of SPIE, 12985, 129850J. https://doi.org/10.1117/12.3023434
2. Mamyrbayev, O.; Momynzhanova, K; Pavlov, S.; Lubov Zagoruyko, L; Oralbekova, D; Zhumagulova, S. System for Automatic Diabetic Retinopathy. Afr.J.Bio.Sc. 6(15) (2024), ISSN: 2663-2187 doi:10.48047/AFJBS.6.15.2024.7898-7902.

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Glaucoma diagnosis

As a result of this study, the first stage of validation for uploaded fundus images was implemented. This verification module is integrated into the web application available to users at https://glaucoma-diag.iict.kz/.