Quantitative assessment of colour fundus photography in hyperopia children based on artificial intelligence
ObjectivesThis study aimed to quantitatively evaluate optic nerve head and retinal vascular parameters in children with hyperopia in relation to age and spherical equivalent refraction (SER) using artificial intelligence (AI)-based analysis of colour fundus photographs (CFP).Methods and analysisThis...
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Veröffentlicht in: | BMJ open ophthalmology 2024-07, Vol.9 (1), p.e001520 |
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Hauptverfasser: | , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | ObjectivesThis study aimed to quantitatively evaluate optic nerve head and retinal vascular parameters in children with hyperopia in relation to age and spherical equivalent refraction (SER) using artificial intelligence (AI)-based analysis of colour fundus photographs (CFP).Methods and analysisThis cross-sectional study included 324 children with hyperopia aged 3–12 years. Participants were divided into low hyperopia (SER+0.5 D to+2.0 D) and moderate-to-high hyperopia (SER≥+2.0 D) groups. Fundus parameters, such as optic disc area and mean vessel diameter, were automatically and quantitatively detected using AI. Significant variables (p |
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ISSN: | 2397-3269 2397-3269 |
DOI: | 10.1136/bmjophth-2023-001520 |