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- Title
Deep Learning Applications to Classification and Detection of Age-Related Macular Degeneration on Optical Coherence Tomography Imaging: A Review.
- Authors
Koseoglu, Neslihan Dilruba; Grzybowski, Andrzej; Liu, T. Y. Alvin
- Abstract
Age-related macular degeneration (AMD) is one of the leading causes of blindness in the elderly, more commonly in developed countries. Optical coherence tomography (OCT) is a non-invasive imaging device widely used for the diagnosis and management of AMD. Deep learning (DL) uses multilayered artificial neural networks (NN) for feature extraction, and is the cutting-edge technique for medical image analysis for diagnostic and prognostication purposes. Application of DL models to OCT image analysis has garnered significant interest in recent years. In this review, we aimed to summarize studies focusing on DL models used in classification and detection of AMD. Additionally, we provide a brief introduction to other DL applications in AMD, such as segmentation, prediction/prognostication, and models trained on multimodal imaging.
- Subjects
MACULAR degeneration; OPTICAL coherence tomography; DEEP learning; ARTIFICIAL neural networks; RETINAL imaging; ELECTRICAL impedance tomography; DIAGNOSTIC imaging
- Publication
Ophthalmology & Therapy, 2023, Vol 12, Issue 5, p2347
- ISSN
2193-8245
- Publication type
Article
- DOI
10.1007/s40123-023-00775-0