ArticleFrontiers in medicine2025
Artificial intelligence-assisted quantification of fundus tessellation in early-onset high myopia.
Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Defining the critical axial length threshold for transition from physiological growth to pathological fundus structural remodeling in adolescent myopia.Frontiers in cell and developmental biology · 2026Article
- Artificial intelligence assisted quantitative analysis of fundus structural and vascular alterations reveals fundus tessellation as a robust biomarker of myopia severity.Frontiers in cell and developmental biology · 2026Article
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Authors and funding
5 authors.
Funding
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Abstract
Purpose: To quantitatively evaluate fundus tessellation density (FTD) in children with early-onset high myopia (eo-HM) using artificial intelligence (AI)-assisted image analysis and to explore its association with axial length (AL). Methods: This cross-sectional study included children aged ≤6 years with eo-HM, defined as spherical equivalent (SE) ≤ -6.00 D and/or AL > 26.00 mm. Cycloplegic refraction, AL measurement, and ultra-widefield fundus photography were performed. A deep learning-based algorithm quantified FTD across concentric macular zones (1 mm, 3 mm, 6 mm) and anatomical sectors. Correlation and multivariate regression analyses were used to assess associations between FTD and AL. Results: A total of 47 eyes from 31 children were analyzed. Mean SE was -9.35 ± 3.74 D and AL was 25.70 ± 1.50 mm. FTD declined from center to periphery ( Conclusion: AI-assisted quantification of FTD provides a sensitive and objective measure of early retinal changes in eo-HM. Regional FTD, especially in nasal and perifoveal regions, is strongly associated with axial elongation and may serve as a useful biomarker for early diagnosis and monitoring of pediatric high myopia.
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