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Topic Collection

Imaging and Biomarkers in Ophthalmology

Ophthalmic imaging methods are crucial for diagnosing and managing various eye pathologies, enabling improved detection and characterization of structural and functional changes in the eye. The application of Artificial Intelligence (AI) and Deep Learning in ophthalmic imaging opens up new possibilities for screening, diagnosis, monitoring, and predicting the progression of ocular conditions. This Topic Collection includes original research on various ophthalmic imaging methods, biomarkers and the use of AI, and Deep Learning techniques in both anterior and posterior segments of the eye.

Original Research

Outer retinal corrugations in late-onset retinal degeneration: a diagnostic finding demonstrated with multimodal imaging (26 October 2023) Holly Joan Duncan, Thomas W McNally, Mariantonia Ferrara, Ajay Kotagiri Impact of smoking on choroidal microvasculature dropout in glaucoma: a cross-sectional study (29 October 2023) Takashi Nishida, Eleonora Micheletti, Kareem Latif, Kelvin H Du, Robert N Weinreb, Sasan Moghimi OCT and OCTA in dysthyroid optic neuropathy: a systematic review and meta-analysis (23 November 2023) Nan Yang, Hui Zhu, Junxin Ma, Qing Shao Colour tone of retinal arterioles imaged with a colour scanning laser ophthalmoscope can be an indicator of systemic arterial stiffness (7 December 2023) Takato Sakono, Hiroto Terasaki, Takuro Kubozono, Shozo Sonoda, Ryoh Funatsu, Naohisa Mihara, Hideki Shiihara, Mitsuru Ohishi,Taiji Sakamoto Real-world evaluation of smartphone-based artificial intelligence to screen for diabetic retinopathy in Dominica: a clinical validation study (22 December 2023) Oliver Kemp, Covadonga Bascaran, Edyta Cartwright, Lauren McQuillan, Nanda Matthew, Hazel Shillingford-Ricketts, Marcia Zondervan, Allen Foster, Matthew Burton Peripapillary retinal nerve fibre layer thinning, perfusion changes and optic neuropathy in carriers of Leber hereditary optic neuropathy-associated mitochondrial variants (11 March 2024) Clare Quigley, Kirk A J Stephenson, Paul F Kenna, Lorraine Cassidy Quantitative assessment of colour fundus photography in hyperopia children based on artificial intelligence (5 July 2024) Ruiyu Luo, Zhirong Wang, Zhidong Li, Rui Xie, Yuan Zhang, Guitong Ye, Jianqi Chen, Yue Xiao, Jinan Zhan, Yingting Zhu, Yehong Zhuo Factors influencing the reliability of measurements in eyes with full-thickness macular holes: are we measuring incorrectly? (17 August 2024) George Moussa, Assad Jalil, Myrta Lippera, Nouf Alnafisee, Tsveta Ivanova Automatic retinal image analysis methods using colour fundus images for screening glaucomatous optic neuropathy (10 September 2024) Chuying Shi, Jack Lee, Di Shi, Gechun Wang, Fei Yuan, Benny Chung-Ying Zee

Guest Editors

Vito Romano University of Brescia ORCID iD logoorcid.org/0000-0002-5148-7643
Mariantonia Ferrara Manchester Royal Eye Hospital ORCID iD logoorcid.org/0000-0002-1191-4989
Jingjing Huang Sun Yat-sen University ORCID iD logoorcid.org/0000-0002-3009-8681
keywords: anterior segment imaging; artificial intelligence; confocal microscopy; corneal biomarkers; multimodal imaging; ophthalmic imaging; optical coherence tomography; posterior segment imaging; retinal biomarkers; specular microscopy