A new method for automatic diagnosis of age-related macular degeneration using optical coherence tomography images

Diseases associated with the retina and macula of the eye, causing permanent loss of vision or a great deal of loss of vision in people, leads to a decrease in the quality of life and a lot of problems in daily life. For this reason, the timely and correct identification of these diseases and disorders has become important. The optical coherence tomography imaging method provides high precision in imaging and good information about the depth of the retina. This imaging technique is a great help in the accurate identification of macular-related diseases. Age-related macular degeneration is one of the most common retinal diseases. The purpose of this study is to design and implement a system that is reliable and fast and can detect the age-related macular degeneration by using optical coherence tomography image processing accurately and accurately and quickly. In these studies, histograms of orientational gradients and principal component analysis for extraction of features and AdaBoost ensemble classification method have been used to classify the data. The database used includes 269 patients and 115 healthy people. All three indicators of accuracy, sensitivity and specificity of the implemented system were measured at 100%.