State of the Art in Retinal Optical Coherence Tomography Images
Deadline for manuscript submissions: 31 March 2024 | Viewed by 2890
Interests: OCT; clinical ophthalmology; ophthalmological diagnostic techniques; eye diseases
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Retinal optical coherence tomography (OCT) is a non-invasive imaging technique that has revolutionized the diagnosis and management of retinal diseases. OCT uses light waves to capture detailed images of the retina, the light-sensitive layer at the back of the eye. These images provide important information about the structure and function of the retina, which can be used to diagnose and monitor a wide range of retinal disorders, including age-related macular degeneration, diabetic retinopathy, and glaucoma.
Recent advancements in OCT technology have greatly improved the resolution and speed of these images, allowing for more accurate and detailed analysis of the retina. New imaging methods, such as swept-source OCT and spectral domain OCT, have increased the axial resolution and speed of the images. This has led to the development of new diagnostic and therapeutic strategies, such as the use of OCT angiography to visualize the blood vessels in the retina.
In addition to improvements in technology, there have also been significant advancements in the use of artificial intelligence (AI) and machine learning (ML) in OCT image analysis. These techniques can be used to automatically detect and quantify retinal disorders, such as age-related macular degeneration and diabetic retinopathy, and to assist in the monitoring of treatment response.
Dr. Adam Wylęgała
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- retinal optical coherence tomography (OCT)
- artificial intelligence (AI)
- machine learning (ML)
- retinal disorders