Bhuiyan Alauddin, Karmakar C, Xiao Di, Ramamohanarao Kotagiri, Kanagasingam Yogi
Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:7392-5. doi: 10.1109/EMBC.2013.6611266.
Age-related macular degeneration (AMD) is a major cause of visual impairment in the elderly and identifying people with the early stages of AMD is important when considering the design and implementation of preventative strategies for late AMD. Quantification of drusen size and total area covered by drusen is an important risk factor for progression. In this paper, we propose a method to detect drusen and quantify drusen size along with the area covered with drusen in macular region from standard color retinal images. We used combined local intensity distribution, adaptive intensity thresholding and edge information to detect potential drusen areas. The proposed method detected the presence of any drusen with 100% accuracy (50/50 images). For drusen detection accuracy (DDA), the segmentations produced by the automated method on individual images achieved mean sensitivity and specificity values of 74.94% and 81.17%, respectively.
年龄相关性黄斑变性（AMD）是老年人视力损害的主要原因，在考虑晚期AMD预防策略的设计和实施时，识别处于AMD早期阶段的人很重要。玻璃膜疣大小的量化以及玻璃膜疣覆盖的总面积是疾病进展的重要风险因素。在本文中，我们提出了一种从标准彩色视网膜图像中检测玻璃膜疣并量化黄斑区域玻璃膜疣大小以及玻璃膜疣覆盖面积的方法。我们使用局部强度分布、自适应强度阈值化和边缘信息相结合的方法来检测潜在的玻璃膜疣区域。所提出的方法检测玻璃膜疣存在的准确率为100%（50/50张图像）。对于玻璃膜疣检测准确率（DDA），自动方法在单个图像上产生的分割结果的平均灵敏度和特异性值分别为74.94%和81.17%。
