Segmentation of Retinal Layers in Diseased Optical Coherence Tomography Scan Images

Abstract

Medical treatments are greatly enhanced by implementing X-rays that help in the suitable development of scanned images and, at this moment, helping in the establishment of the three-dimensional structures for increasing the doctors' performance through accurate visualization. The increase in performance is more greatly enhanced by establishing machine learning models that help develop the predictive results for increasing data outcomes in a broader approach. Moreover, the use of OCT helps in the development of scanned images for the eyes, heart, brain, and other internal organs that prove to be effective in the establishment of proper medical treatments. Human eyes are important parts of the human body. They not only provide vision to humans and provide a learning mechanism for our brain. Neurons get trained for new objects seen by eyes. Retinal Optical Coherence Tomographical imaging provides early detection of retinal diseases which may cause blindness.  The ophthalmologist uses the OCT imaging technique for the diagnosis of retinal diseases in the early stages. The segmentation of retinal layers could easily identify the severity of retinal diseases.