Instituto de Informatica, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
Comput Biol Med. 2010 Feb;40(2):124-37. doi: 10.1016/j.compbiomed.2009.11.009. Epub 2009 Dec 31.
The identification of some important retinal anatomical regions is a prerequisite for the computer aided diagnosis of several retinal diseases. In this paper, we propose a new adaptive method for the automatic segmentation of the optic disk in digital color fundus images, using mathematical morphology. The proposed method has been designed to be robust under varying illumination and image acquisition conditions, common in eye fundus imaging. Our experimental results based on two publicly available eye fundus image databases are encouraging, and indicate that our approach potentially can achieve a better performance than other known methods proposed in the literature. Using the DRIVE database (which consists of 40 retinal images), our method achieves a success rate of 100% in the correct location of the optic disk, with 41.47% of mean overlap. In the DIARETDB1 database (which consists of 89 retinal images), the optic disk is correctly located in 97.75% of the images, with a mean overlap of 43.65%.
一些重要视网膜解剖区域的识别是计算机辅助诊断几种视网膜疾病的前提。在本文中，我们提出了一种新的自适应方法，用于使用数学形态学自动分割数字彩色眼底图像中的视盘。所提出的方法旨在在眼底成像中常见的不同光照和图像采集条件下具有鲁棒性。我们基于两个公开可用的眼底图像数据库的实验结果令人鼓舞，表明我们的方法有可能比文献中提出的其他已知方法实现更好的性能。使用 DRIVE 数据库（包含 40 张视网膜图像），我们的方法在视盘的正确位置上的成功率达到 100％，平均重叠率为 41.47％。在 DIARETDB1 数据库（包含 89 张视网膜图像）中，97.75％的图像正确定位了视盘，平均重叠率为 43.65％。
