Age-related macular degeneration (AMD) is a leading cause of blindness worldwide and is expected to affect approximately 288 million people globally by 2040. While multimodal imaging has traditionally been the gold standard for diagnosing AMD, optical Coherence Tomography (OCT) provides high-resolution, non-invasive imaging of the retina and has become central to routine disease management. Artificial intelligence (AI) has rapidly emerged as a transformative force across various domains, with its impact particularly notable in ophthalmology and retina imaging, which has opened new avenues for improving diagnostic accuracy, predicting disease progression, and optimizing treatment plans. AI-based algorithms hold great potential for accurately quantifying biomarkers, such as fluid volume and geographic atrophy area in OCT images, predicting disease progression, and assisting in treatment decisions both in clinical practice and academic research. This chapter provides an overview of the current state of AI applications in AMD, highlighting its potential, the challenges encountered, and future prospects in the field. Author(s) Details Virginia Mares Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria and Department of Ophthalmology, Federal University of Minas Gerais, Belo Horizonte, Brazil. Marcio B. Nehemy Department of Ophthalmology, Federal University of Minas Gerais, Belo Horizonte, Brazil. Hrvoje Bogunovic Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria. Sophie Frank Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria. Gregor S. Reiter Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria. Ursula Schmidt-Erfurth Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria. Please see the book here:- https://doi.org/10.9734/bpi/srnta/v6/1942

 

Age-related macular degeneration (AMD) is a leading cause of blindness worldwide and is expected to affect approximately 288 million people globally by 2040. While multimodal imaging has traditionally been the gold standard for diagnosing AMD, optical Coherence Tomography (OCT) provides high-resolution, non-invasive imaging of the retina and has become central to routine disease management. Artificial intelligence (AI) has rapidly emerged as a transformative force across various domains, with its impact particularly notable in ophthalmology and retina imaging, which has opened new avenues for improving diagnostic accuracy, predicting disease progression, and optimizing treatment plans. AI-based algorithms hold great potential for accurately quantifying biomarkers, such as fluid volume and geographic atrophy area in OCT images, predicting disease progression, and assisting in treatment decisions both in clinical practice and academic research. This chapter provides an overview of the current state of AI applications in AMD, highlighting its potential, the challenges encountered, and future prospects in the field.

 

 

Author(s) Details

Virginia Mares

Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria and Department of Ophthalmology, Federal University of Minas Gerais, Belo Horizonte, Brazil.

Marcio B. Nehemy

Department of Ophthalmology, Federal University of Minas Gerais, Belo Horizonte, Brazil.

Hrvoje Bogunovic

Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.

Sophie Frank

Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.

Gregor S. Reiter

Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.

Ursula Schmidt-Erfurth

Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.

 

 

Please see the book here:- https://doi.org/10.9734/bpi/srnta/v6/1942