Automatic Segmentation of Diffuse Retinal Thickening Edemas Using Optical Coherence Tomography Images

Abstract

[Abstract]: Diabetic retinopathy is one of the leading causes of vision impairment that is commonly associated to the Macular Edema (ME) disease. The Diffuse Retinal Thickening (DRT) is a ME type derived from the local intraretinal fluid accumulation in the lower retinal layers, producing significant morphological alterations in the eye fundus. The presence and properties of these intraretinal fluids are used by the ophthalmologists as significant indicators of the clinical stage of the ME disease. Given that, the precise identification and segmentation of the DRT edema type allow the early diagnosis of the ME disease which, therefore, permits a better adjustment of the treatments, reducing their costs as well as improving the life quality of the patients.

This paper proposes a novel methodology for the automatic identification and segmentation of the DRT edemas using Optical Coherence Tomography (OCT) images as source of information. Firstly, the method identifies four of the principal retinal layers that are used as reference to delimit the outer retina, region where the DRT edemas are typically originated. Inside this region, a large and heterogeneous set of features was defined to recognize the characteristic “sponge-like” patterns of the DRT edema, using intensity, texture and clinically-defined features. For this analysis, four representative classifiers were employed with the best subsets of previously selected features. This methodology was tested using 70 OCT images from where 560 samples were extracted with the presence and absence of DRT edemas. The best results were achieved by the 7-kNN classifier, reaching in the detection stage an accuracy of 0.9366, whereas in the segmentation stage obtained values of 0.6625 and 0.7899 for the Jaccard and Dice coefficients, respectively.