Abstract

Retinal microaneurysms (MAs) are the earliest clinically observable lesions of diabetic retinopathy. Reliable automated MAs detection is thus critical for early diagnosis of diabetic retinopathy. This paper proposes a novel method for the automated MAs detection in color fundus images based on gradient vector analysis and class imbalance classification, which is composed of two stages, i.e. candidate MAs extraction and classification. In the first stage, a candidate MAs extraction algorithm is devised by analyzing the gradient field of the image, in which a multi-scale log condition number map is computed based on the gradient vectors for vessel removal, and then the candidate MAs are localized according to the second order directional derivatives computed in different directions. Due to the complexity of fundus image, besides a small number of true MAs, there are also a large amount of non-MAs in the extracted candidates. Classifying the true MAs and the non-MAs is an extremely class imbalanced classification problem. Therefore, in the second stage, several types of features including geometry, contrast, intensity, edge, texture, region descriptors and other features are extracted from the candidate MAs and a class imbalance classifier, i.e., RUSBoost, is trained for the MAs classification. With the Retinopathy Online Challenge (ROC) criterion, the proposed method achieves an average sensitivity of 0.433 at 1/8, 1/4, 1/2, 1, 2, 4 and 8 false positives per image on the ROC database, which is comparable with the state-of-the-art approaches, and 0.321 on the DiaRetDB1 V2.1 database, which outperforms the state-of-the-art approaches.

Highlights

  • Diabetic retinopathy (DR) is the commonest complication of diabetes and one of the major causes of blindness

  • We evaluate our method with the free-response receiver operating characteristic (FROC) curve [3] and the partial area under the curve (AUC) of the FROC curve [25]

  • This paper proposed a novel automated method for MAs detection in color fundus images, which contains two stages, i.e. candidate MAs extraction and classification

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Summary

Introduction

Diabetic retinopathy (DR) is the commonest complication of diabetes and one of the major causes of blindness. The early diagnosis and treatment of DR are very important to prevent vision impairment. The microaneurysms (MAs) on retina are the small saccular bulges in the walls of retinal capillary vessels [1] and generally appear near to the macula [2]. MAs are the first sign of DR [3]. According to the Early Treatment Diabetic Retinopathy Study (ETDRS).

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