An Ensemble-Based System for Microaneurysm Detection and Diabetic Retinopathy Grading
An Ensemble-Based System for Microaneurysm Detection and Diabetic Retinopathy Grading
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DOI：
10.1109/tbme.2012.2193126
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发表时间：
2012-06-01
影响因子：
4.6
通讯作者：
Hajdu, Andras
中科院分区：
文献类型：
--
作者：
Antal, Balint;Hajdu, Andras
数字眼底图像中微动脉瘤的可靠检测仍然是医学图像处理中的一个悬而未决的问题。我们提出了一个基于集成的框架，以提高微动脉瘤检测。与考虑多个分类器的输出的众所周知的方法不同，我们提出了微动脉瘤检测器的内部组件的组合，即预处理方法和候选提取器。我们已经在在线竞赛中评估了我们的微动脉瘤检测方法，该算法目前排名第一，并且在其他两个数据库中也是如此。由于微动脉瘤检测在糖尿病视网膜病变（DR）分级中具有决定性作用，因此我们还在公开可用的Messidor数据库上测试了该任务的拟议方法，其中在“DR/非DR”类型分类中实现了有希望的AUC 0.90+/-0.01
Reliable microaneurysm detection in digital fundus images is still an open issue in medical image processing. We propose an ensemble-based framework to improve microaneurysm detection. Unlike the well-known approach of considering the output of multiple classifiers, we propose a combination of internal components of microaneurysm detectors, namely preprocessing methods and candidate extractors. We have evaluated our approach for microaneurysm detection in an online competition, where this algorithm is currently ranked as first, and also on two other databases. Since microaneurysm detection is decisive in diabetic retinopathy (DR) grading, we also tested the proposed method for this task on the publicly available Messidor database, where a promising AUC 0.90+/-0.01 is achieved in a "DR/non-DR"-type classification