Automatic Identification of Diabetic Macular Edema Biomarkers Using Optical Coherence Tomography Scans

Abstract

[Abstract]: Optical Coherence Tomography (OCT) imaging has revolutionized the daily clinical practice, especially in the field of ophthalmology. Diabetic Macular Edema (DME) is one of the most important complications of diabetes and a leading cause of preventable blindness in the developed countries. In this way, a precise identification and analysis of DME biomarkers allow the clinical specialists to make a more accurate diagnosis and treatment of this relevant ocular disease.

Thus, in this work, we present a computational system for the automatic identification and extraction of DME biomarkers by the analysis of OCT scans, following the clinical classification of reference in the ophthalmological field. The presented method was validated using a dataset composed by 40 OCT images that were retrieved from different patients. Satisfactory results were obtained, providing a consistent and coherent set of different computational biomarkers that can help the clinical specialists in their diagnostic procedures.