Using deep learning to diagnose retinal diseases through medical image analysis
Azhibekova Z. Bekbayeva R. Yussupova G. Kaibassova D. Ostretsova I. Muratbekova S. Kakabayev A. Sultanova Z.
December 2024Institute of Advanced Engineering and Science
International Journal of Electrical and Computer Engineering
2024#14Issue 66455 - 6465 pp.
The scientific article focuses on the application of deep learning through simple U-Net, attention U-Net, residual U-Net, and residual attention U-Net models for diagnosing retinal diseases based on medical image analysis. The work includes a thorough analysis of each models ability to detect retinal pathologies, taking into account their unique characteristics such as attention mechanisms and residual connections. The obtained experimental results confirm the high accuracy and reliability of the proposed models, emphasizing their potential as effective tools for automated diagnosis of retinal diseases based on medical images. This approach opens up new prospects for improving diagnostic procedures and increasing the efficiency of medical practice. The authors of the article propose an innovative method that can significantly facilitate the process of identifying retinal diseases, which is critical for early diagnosis and timely treatment. The results of the study support the prospect of using these models in clinical practice, highlighting their ability to accurately analyze medical images and improve the quality of eye health care.
Analyze medical images , Attention U-Net , Deep learning , Residual attention U-Net , Residual U-Net , Simple U-Net
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Department of Information and Communication Technologies, Non-profit Joint Stock Company S. D. Asfendiyarov Kazakh, National Medical University, Almaty, Kazakhstan
Department of Automation, Information Technology and Urban Development, Non-Profit Limited Company, Semey University named after Shakarim, Semey, Kazakhstan
Faculty of Construction Technologies, Infrastructure and Management, International Educational Corporation, Almaty, Kazakhstan
Department of Computer Engineering, Astana IT University, Astana, Kazakhstan
Pedagogical Institute, Sh. Ualikhanov Kokshetau University, Kokshetau, Kazakhstan
Higher School of Medicine, Sh. Ualikhanov Kokshetau University, Kokshetau, Kazakhstan
Agrotechnical Institute named after S. Sadvakasov, Sh. Ualikhanov Kokshetau University, Kokshetau, Kazakhstan
Department of Biostatistics, Bioinformatics, and Information Technologies, Astana Medical University, Astana, Kazakhstan
Department of Information and Communication Technologies
Department of Automation
Faculty of Construction Technologies
Department of Computer Engineering
Pedagogical Institute
Higher School of Medicine
Agrotechnical Institute named after S. Sadvakasov
Department of Biostatistics
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