Retinopathy Online Challenge: Automatic Detection of Microaneurysms in Digital Color Fundus Photographs
Retinopathy Online Challenge: Automatic Detection of Microaneurysms in Digital Color Fundus Photographs
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DOI：
10.1109/tmi.2009.2033909
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发表时间：
2010-01-01
影响因子：
10.6
通讯作者：
Abramoff, Michael D.
中科院分区：
文献类型：
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作者：
Niemeijer, Meindert;van Ginneken, Bram;Abramoff, Michael D.
数字彩色眼底照片中微动脉瘤的检测是糖尿病视网膜病变(DR)自动筛查的关键第一步，DR是糖尿病的常见并发症。为了实现这一检测，过去已经发表了许多方法，但没有一种方法在相同的数据上进行相互比较。在这项工作中，我们介绍了第一届国际微动脉瘤检测比赛的结果，该比赛是在视网膜病变在线挑战赛(ROC)的背景下组织的，ROC是一项针对DR检测各个方面的多年在线比赛。在这场比赛中，我们比较了五种不同方法的结果，这些方法是由五个不同的研究团队对同一组数据产生的。使用本工作中提出的算法以统一的方式进行评估。比赛使用的数据集包括50张训练图像和50张测试图像，其中组织者(M.Niemeijer、B.van Ginneken和M.D.Abramoff)取消了参考标准。通过网站提交关于测试数据的结果，然后使用标准化评价软件确定每种方法的执行情况。一位人类专家在测试集中检测到了微动脉瘤，以便与自动方法的性能进行比较。总体结果表明，无论是自动方法还是人类专家，微动脉瘤的检测都是一项具有挑战性的任务。有改进的余地，因为表现最好的系统达不到人类专家的表现。与中华民国微动脉瘤检测大赛相关的资料将继续公开，网站将继续接受投稿。
The detection of microaneurysms in digital color fundus photographs is a critical first step in automated screening for diabetic retinopathy (DR), a common complication of diabetes. To accomplish this detection numerous methods have been published in the past but none of these was compared with each other on the same data. In this work we present the results of the first international microaneurysm detection competition, organized in the context of the Retinopathy Online Challenge (ROC), a multi-year online competition for various aspects of DR detection. For this competition, we compare the results of five different methods, produced by five different teams of researchers on the same set of data. The evaluation was performed in a uniform manner using an algorithm presented in this work. The set of data used for the competition consisted of 50 training images with available reference standard and 50 test images where the reference standard was witheld by the organizers (M. Niemeijer, B. van Ginneken, and M. D. Abramoff). The results obtained on the test data was submitted through a website after which standardized evaluation software was used to determine the performance of each of the methods. A human expert detected microaneurysms in the test set to allow comparison with the performance of the automatic methods. The overall results show that microaneurysm detection is a challenging task for both the automatic methods as well as the human expert. There is room for improvement as the best performing system does not reach the performance of the human expert. The data associated with the ROC microaneurysm detection competition will remain publicly available and the website will continue accepting submissions.