A Review of Glaucoma Detection from Digital Fundus Images using Machine Learning Techniques

Glaucoma represents one of the leading causes of irreversible vision loss as it affects the optic nerve fibers and astrocytes. The early detection of glaucoma has recently become an important factor in the medical field and, among various types of eye exams, retinal imaging provides an accurate visualization of the important structures of the eye. In this paper, it was realized a review of the most relevant techniques based on machine learning, deep learning and transfer learning for retinal image analysis including their advantages and disadvantage.