Advancements in Glaucoma Diagnosis: The Role of AI in Medical Imaging

• Published in: Diagnostics (Basel) Vol. 14; no. 5; p. 530
• Main Authors: Bragança, Clerimar Paulo, Torres, José Manuel, Macedo, Luciano Oliveira, Soares, Christophe Pinto de Almeida
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.03.2024; MDPI
• Subjects: Algorithms; Artificial intelligence; Asymmetry; Data mining; deep learning; Epidemiology; Glaucoma; image analysis; Image processing; Machine learning; Medical imaging equipment; Medical personnel; Medical research; Medicine, Experimental; Ophthalmology; Optics; Retina; Review; deep learning; image analysis; glaucoma; artificial intelligence
• ISSN: 2075-4418; 2075-4418
• DOI: 10.3390/diagnostics14050530

The progress of artificial intelligence algorithms in digital image processing and automatic diagnosis studies of the eye disease glaucoma has been growing and presenting essential advances to guarantee better clinical care for the population. Given the context, this article describes the main types of glaucoma, traditional forms of diagnosis, and presents the global epidemiology of the disease. Furthermore, it explores how studies using artificial intelligence algorithms have been investigated as possible tools to aid in the early diagnosis of this pathology through population screening. Therefore, the related work section presents the main studies and methodologies used in the automatic classification of glaucoma from digital fundus images and artificial intelligence algorithms, as well as the main databases containing images labeled for glaucoma and publicly available for the training of machine learning algorithms.