Instituto de Informática, Universidade Federal do Rio Grande do Sul, Av. Bento Gonalves 9500, Porto Alegre, RS, Brazil.
Comput Med Imaging Graph. 2010 Apr;34(3):228-35. doi: 10.1016/j.compmedimag.2009.10.001. Epub 2009 Dec 1.
The detection of exudates is a prerequisite for detecting and grading severe retinal lesions, like the diabetic macular edema. In this work, we present a new method based on mathematical morphology for detecting exudates in color eye fundus images. A preliminary evaluation of the proposed method performance on a known public database, namely DIARETDB1, indicates that it can achieve an average sensitivity of 70.48%, and an average specificity of 98.84%. Comparing to other recent automatic methods available in the literature, our proposed approach potentially can obtain better exudate detection results in terms of sensitivity and specificity.
渗出物的检测是检测和分级严重视网膜病变（如糖尿病性黄斑水肿）的前提。在这项工作中，我们提出了一种基于数学形态学的新方法，用于检测彩色眼底图像中的渗出物。在一个已知的公共数据库 DIARETDB1 上对所提出方法性能的初步评估表明，它可以实现平均灵敏度 70.48%，平均特异性 98.84%。与文献中其他最近的自动方法相比，我们提出的方法在灵敏度和特异性方面可能具有更好的渗出物检测结果。
