Major advances in diagnostic technologies are offering unprecedented insight into the
condition of the retina and beyond ocular disease. Digital images providing millions of …

Obtaining expert labels in clinical imaging is difficult since exhaustive annotation is time-
consuming. Furthermore, not all possibly relevant markers may be known and sufficiently …

Abstract Diabetic Macular Edema (DME) is a potentially blinding consequence of Diabetic
Retinopathy (DR) as well as the leading cause of vision loss in diabetics. DME is …

Abstract Background and Objective Retinal diseases are becoming a major health problem
in recent years. Their early detection and ensuing treatment are essential to prevent visual …

As the labeled anomalous medical images are usually difficult to acquire, especially for rare
diseases, the deep learning based methods, which heavily rely on the large amount of …

Diagnosis and treatment guidance are aided by detecting relevant biomarkers in medical
images. Although supervised deep learning can perform accurate segmentation of …

Macular edema (ME) is one of the most common retinal diseases that occur as a result of the
detachment of the retinal layers on the macula. This study provides computer-aided …

Diabetic Retinopathy (DR) represents a highly-prevalent complication of diabetes in which
individuals suffer from damage to the blood vessels in the retina. The disease manifests …

Supervised deep learning has achieved prominent success in various diabetic macular
edema (DME) recognition tasks from optical coherence tomography (OCT) volumetric …

Medical images play a very important role in making the right diagnosis for the doctor and in
the patient's treatment process. Using intelligent algorithms makes it possible to quickly …