Deep Learning in Neovascular Age-Related Macular Degeneration

被引：2

作者：

Borrelli, Enrico ^{[1
,2
]}

Serafino, Sonia ^{[1
,2
]}

Ricardi, Federico ^{[1
,2
]}

Coletto, Andrea ^{[1
,2
]}

Neri, Giovanni ^{[1
,2
]}

Olivieri, Chiara ^{[1
,2
]}

Ulla, Lorena ^{[1
,2
]}

Foti, Claudio ^{[1
,2
]}

Marolo, Paola ^{[1
,2
]}

Toro, Mario Damiano ^{[3
]}

Bandello, Francesco ^{[4
,5
]}

Reibaldi, Michele ^{[1
,2
]}

机构：

[1] Univ Turin, Dept Surg Sci, Div Ophthalmol, Via Verdi 8, I-10124 Turin, Italy

[2] City Hlth & Sci Hosp, Dept Ophthalmol, I-10126 Turin, Italy

[3] Univ Naples Federico II, Publ Hlth Dept, Eye Clin, I-80138 Naples, Italy

[4] Univ Vita Salute San Raffaele, Dept Ophthalmol, I-20132 Milan, Italy

[5] IRCCS San Raffaele Sci Inst, I-20132 Milan, Italy

来源：

MEDICINA-LITHUANIA | 2024年 / 60卷 / 06期

关键词：

age-related macular degeneration; optical coherence tomography; neovascularization; neovascular age-related macular degeneration; artificial intelligence; deep learning; biomarker; TOMOGRAPHIC HYPERREFLECTIVE FOCI; PIGMENT EPITHELIAL DETACHMENT; ANTI-VEGF TREATMENT; DIABETIC-RETINOPATHY; INTRAVITREAL BEVACIZUMAB; AUTOMATED DETECTION; VISUAL OUTCOMES; PREDICTION; QUANTIFICATION; ASSOCIATION;

D O I：

10.3390/medicina60060990

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

Background and objectives: Age-related macular degeneration (AMD) is a complex and multifactorial condition that can lead to permanent vision loss once it progresses to the neovascular exudative stage. This review aims to summarize the use of deep learning in neovascular AMD. Materials and Methods: Pubmed search. Results: Deep learning has demonstrated effectiveness in analyzing structural OCT images in patients with neovascular AMD. This review outlines the role of deep learning in identifying and measuring biomarkers linked to an elevated risk of transitioning to the neovascular form of AMD. Additionally, deep learning techniques can quantify critical OCT features associated with neovascular AMD, which have prognostic implications for these patients. Incorporating deep learning into the assessment of neovascular AMD eyes holds promise for enhancing clinical management strategies for affected individuals. Conclusion: Several studies have demonstrated effectiveness of deep learning in assessing neovascular AMD patients and this has a promising role in the assessment of these patients.

引用

页数：11

共 77 条

[1] Automatic recognition of severity level for diagnosis of diabetic retinopathy using deep visual features [J].