Research Paper on The Early Detection, Diagnosis, and Grading of Retinal Diseases: A Survey of the Role of Medical Image Modalities and AI

Description

Title: The Early Detection, Diagnosis, and Grading of Retinal Diseases: A Survey of the Role of Medical Image Modalities and AI

Abstract: Age-related macular degeneration (AMD), diabetic retinopathy (DR), diabetic macular edema (DME), retinal tear, epiretinal membrane, macular hole, retinal detachment, retinitis pigmentosa, and retinal vein occlusion are some of the diseases that can be detected using traditional dilated ophthalmoscopy (RVO), and occluded retinal arteries (RAO). Among these conditions, AMD and DR are the main contributors to progressive vision loss, with the latter being acknowledged as an epidemic on a global scale. The diagnosis and treatment of DR and AMD have been improved by developments in retinal imaging. In this review article, the role of artificial intelligence (AI) in providing automated detection, diagnosis, and staging of these diseases will be surveyed. We will concentrate on the various imaging modalities for accurate diagnosis, early detection, and staging of both AMD and DR. Furthermore, a summary and discussion of recent works is provided. Finally, upcoming trends are described. The research conducted for this survey shows the usefulness of AI in the early diagnosis, staging, and treatment of DR and/or AMD. More AI solutions that have the potential to be used in clinical settings will be introduced in the future.

Keywords: retinal diseases; artificial intelligence; diabetic retinopathy; macular degeneration; modalities

Paper Quality: SCOPUS / Web of Science Level Research Paper

Subject: Bioengineering

Writer Experience: 20+ Years

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