Effective Fundus Image Decomposition for the Detection of Red Lesions and Hard Exudates to Aid in the Diagnosis of Diabetic Retinopathy.

Roberto Romero-Oraá,María I López-Gálvez,Javier Oraá-Pérez,María García,Roberto Hornero

doi:10.3390/s20226549

Abstract

Diabetic retinopathy (DR) is characterized by the presence of red lesions (RLs), such as microaneurysms and hemorrhages, and bright lesions, such as exudates (EXs). Early DR diagnosis is paramount to prevent serious sight damage. Computer-assisted diagnostic systems are based on the detection of those lesions through the analysis of fundus images. In this paper, a novel method is proposed for the automatic detection of RLs and EXs. As the main contribution, the fundus image was decomposed into various layers, including the lesion candidates, the reflective features of the retina, and the choroidal vasculature visible in tigroid retinas. We used a proprietary database containing 564 images, randomly divided into a training set and a test set, and the public database DiaretDB1 to verify the robustness of the algorithm. Lesion detection results were computed per pixel and per image. Using the proprietary database, 88.34% per-image accuracy (ACCi), 91.07% per-pixel positive predictive value (PPVp), and 85.25% per-pixel sensitivity (SEp) were reached for the detection of RLs. Using the public database, 90.16% ACCi, 96.26% PPV_p, and 84.79% SEp were obtained. As for the detection of EXs, 95.41% ACCi, 96.01% PPV_p, and 89.42% SE_p were reached with the proprietary database. Using the public database, 91.80% ACCi, 98.59% PPVp, and 91.65% SEp were obtained. The proposed method could be useful to aid in the diagnosis of DR, reducing the workload of specialists and improving the attention to diabetic patients.

Highlights

Diabetic retinopathy (DR) is a microvascular complication of diabetes mellitus [1,2]
Examinations based on the analysis of color fundus images to detect the characteristic signs of the DR: red lesions (RLs), such as microaneurysms (MAs) and hemorrhages (HEs), and bright lesions, such as Sensors 2020, 20, 6549; doi:10.3390/s20226549
We have found four methods that have been evaluated using the DiaretDB1 database in order to establish a direct comparison with the proposed method for RL detection

Summary

Introduction

Diabetic retinopathy (DR) is a microvascular complication of diabetes mellitus [1,2] While it is asymptomatic in its initial stage, it leads progressively to vision loss [2]. In order to detect the visible lesions in fundus it is important to separate the background and the foreground. The foreground covers the main information and is composed of dark pixels and and the foreground. We eliminated the dark pixels in to obtain fundus image using our method in to obtain prepobtain thethe image using our method in [42]. We eliminated the dark pixels in I to the image and eliminated the bright pixels obtainthe theimage imageI IIbg−dark.

Methods

Discussion

Conclusion