Abstract
Age-related macular degeneration (AMD) is a retinal disorder affecting the elderly, and society’s aging population means that the disease is becoming increasingly prevalent. The vision in patients with early AMD is usually unaffected or nearly normal but central vision may be weakened or even lost if timely treatment is not performed. Therefore, early diagnosis is particularly important to prevent the further exacerbation of AMD. This paper proposed a novel automatic detection method of AMD from optical coherence tomography (OCT) images based on deep learning and a local outlier factor (LOF) algorithm. A ResNet-50 model with L2-constrained softmax loss was retrained to extract features from OCT images and the LOF algorithm was used as the classifier. The proposed method was trained on the UCSD dataset and tested on both the UCSD dataset and Duke dataset, with an accuracy of 99.87% and 97.56%, respectively. Even though the model was only trained on the UCSD dataset, it obtained good detection accuracy when tested on another dataset. Comparison with other methods also indicates the efficiency of the proposed method in detecting AMD.
Highlights
Age-related macular degeneration (AMD) is the fourth most prevalent ocular disease resulting in vision loss in the macula [1]
The results suggest that the proposed method performed very well compared with previous models when classifying AMD and normal optical coherence tomography (OCT) images
A novel automatic detection method was presented for the detection of AMD from OCT images based on deep learning and an outlier detection method
Summary
Age-related macular degeneration (AMD) is the fourth most prevalent ocular disease resulting in vision loss in the macula [1]. The macula is located in the optical center of the human eye and is an important part of the retina It is required for reading, driving, watching TV, and performing many other daily activities [2]. In wet AMD, patients may see dark spots in their central vision due to blood or fluid leakage under the macula. The main pathogenesis of wet AMD is choroidal neovascularization (CNV), which occurs under the retina and macula. This neovascularization may lead to macular swelling and a reversible loss of vision, or bleeding, which can be highly toxic to the overlying photoreceptors, sometimes even causing irreversible vision loss [6,7]. Regular screening of the retina is crucial for the diagnosis and treatment of AMD and the prevention of further deterioration
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