Digital retinal imaging is a challenging screening method for which effective, robust and cost-effective approaches are still to be developed. Regular screening for diabetic retinopathy and diabetic maculopathy diseases is necessary in order to identify the group at risk of visual impairment. This paper presents a novel automatic detection of diabetic retinopathy and maculopathy in eye fundus images by employing fuzzy image processing techniques. The paper first introduces the existing systems for diabetic retinopathy screening, with an emphasis on the maculopathy detection methods. The proposed medical decision support system consists of four parts, namely: image acquisition, image preprocessing including four retinal structures localisation, feature extraction and the classification of diabetic retinopathy and maculopathy. A combination of fuzzy image processing techniques, the Circular Hough Transform and several feature extraction methods are implemented in the proposed system. The paper also presents a novel technique for the macula region localisation in order to detect the maculopathy. In addition to the proposed detection system, the paper highlights a novel online dataset and it presents the dataset collection, the expert diagnosis process and the advantages of our online database compared to other public eye fundus image databases for diabetic retinopathy purposes.

中文翻译：

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使用模糊图像处理功能对糖尿病性视网膜病变和黄斑病变进行自动筛选和分类。

数字视网膜成像是一种具有挑战性的筛查方法，其有效，鲁棒和具有成本效益的方法尚待开发。定期筛查糖尿病性视网膜病变和糖尿病性黄斑病变疾病是必要的，以便确定有视力障碍风险的人群。本文提出了一种通过使用模糊图像处理技术自动检测眼底图像中的糖尿病性视网膜病变和黄斑病变的方法。本文首先介绍了现有的糖尿病性视网膜病变筛查系统，重点是黄斑病变检测方法。拟议的医疗决策支持系统包括四个部分，即：图像采集，图像预处理（包括四个视网膜结构定位），特征提取以及糖尿病性视网膜病变和黄斑病变的分类。该系统实现了模糊图像处理技术，圆形霍夫变换和几种特征提取方法的结合。本文还提出了一种用于黄斑区域定位的新技术，以检测黄斑病。除了提出的检测系统外，本文还重点介绍了一个新颖的在线数据集，并介绍了该数据集的收集，专家诊断过程以及与其他公众眼底图像数据库相比，我们的在线数据库在糖尿病性视网膜病变方面的优势。