Peer-Reviewed Publication
Surv Ophthalmol2026October 16, 2026Journal Article
Artificial intelligence (AI) and the choroidal challenge: A comprehensive review of AI applications in choroidal imaging.
Oscar Matteo Gagliardi1, Jay Chhablani2, Marco Lupidi3, Maria Carmela Saturno4, Alessandro Lambiase4, Danilo Iannetta5
1Department of Sense Organs, Medicine and Dentistry Faculty, Sapienza University of Rome, Viale del Policlinico 155, 00161 Rome, Italy; Department of Ophthalmology, UPMC Eye Center, University of Pittsburgh, 15129 Pittsburgh, PA, USA.
2Department of Ophthalmology, UPMC Eye Center, University of Pittsburgh, 15129 Pittsburgh, PA, USA.
3Eye Clinic, Department of Experimental and Clinical Medicine, Polytechnic University of Marche, 60126 Ancona, Italy; Fondazione Italiana Macula ETS, Di.N.O.G.Mi., University Eye Clinic, 16132 Genova, Italy.
4Department of Sense Organs, Medicine and Dentistry Faculty, Sapienza University of Rome, Viale del Policlinico 155, 00161 Rome, Italy.
5Department of Sense Organs, Medicine and Dentistry Faculty, Sapienza University of Rome, Viale del Policlinico 155, 00161 Rome, Italy. Electronic address: danilo.iannetta@uniroma1.it.
Abstract
The choroid is a densely vascular layer that sustains the outer retina and may reflect systemic microvascular health. With the advent of new imaging techniques, choroidal imaging has become increasingly detailed, generating vast data volumes. Conventional analytic tools often fall short in managing these high-dimensional datasets. Artificial intelligence (AI) automatically enhances, segments, and…
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