Publication

Abstract : Diabetic retinopathy (DR) is a serious microvascular complication of diabetes mellitus and a very prevalent cause of vision loss worldwide. Fundus Images till now is used as gold standard for DR diagnosis. However, Optical Coherence Tomography (OCT) has emerged as a better option for imaging modality for the early detection, monitoring, and management of DR other than fundus imaging. By providing high-resolution cross-sectional images of the retina, OCT enables visualization of microstructural changes associated with DR, such as retinal thickening, intra-retinal cysts, and disruptions in the retinal layers. The study demonstrates the potential application of two-phase machine learning algorithm techniques for OCT picture classification, leading to more accurate and efficient diagnosis of DR. In recent years, advancements in OCT technology, particularly Optical Coherence Tomographic Angiography (OCTA), have further enhanced ability to assess the retinal microvasculature non-invasively. This paper presents a thorough review of OCT imaging’s function in Diabetic Retinopathy, highlighting its value for treatment monitoring, disease stage, and early identification.