Zhang Zhuo, Liu Jiang, Cherian Neetu Sara, Sun Ying, Lim Joo Hwee, Wong Wing Kee, Tan Ngan Meng, Lu Shijian, Li Huiqi, Wong Tien Ying
Institute for Infocomm Research, A*STAR, Singapore.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:1441-4. doi: 10.1109/IEMBS.2009.5332913.
Glaucoma is the second leading cause of blindness. Glaucoma can be diagnosed through measurement of neuro-retinal optic cup-to-disc ratio (CDR). Automatic calculation of optic cup boundary is challenging due to the interweavement of blood vessels with the surrounding tissues around the cup. A Convex Hull based Neuro-Retinal Optic Cup Ellipse Optimization algorithm improves the accuracy of the boundary estimation. The algorithm's effectiveness is demonstrated on 70 clinical patient's data set collected from Singapore Eye Research Institute. The root mean squared error of the new algorithm is 43% better than the ARGALI system which is the state-of-the-art. This further leads to a large clinical evaluation of the algorithm involving 15 thousand patients from Australia and Singapore.
青光眼是导致失明的第二大主要原因。青光眼可通过测量神经视网膜视杯与视盘比率（CDR）来诊断。由于血管与视杯周围组织相互交织，自动计算视杯边界具有挑战性。一种基于凸包的神经视网膜视杯椭圆优化算法提高了边界估计的准确性。该算法的有效性在从新加坡眼科研究所收集的70例临床患者数据集上得到了验证。新算法的均方根误差比当前最先进的ARGALI系统低43%。这进一步促使对该算法进行大规模临床评估，涉及来自澳大利亚和新加坡的15000名患者。
