Zhang Zhuo, Yin Feng Shou, Liu Jiang, Wong Wing Kee, Tan Ngan Meng, Lee Beng Hai, Cheng Jun, Wong Tien Yin
Institute for Infocomm Research, A*STAR, Singapore.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:3065-8. doi: 10.1109/IEMBS.2010.5626137.
Retinal fundus image is an important modality to document the health of the retina and is widely used to diagnose ocular diseases such as glaucoma, diabetic retinopathy and age-related macular degeneration. However, the enormous amount of retinal data obtained nowadays mostly stored locally; and the valuable embedded clinical knowledge is not efficiently exploited. In this paper we present an online depository, ORIGA(-light), which aims to share clinical groundtruth retinal images with the public; provide open access for researchers to benchmark their computer-aided segmentation algorithms. An in-house image segmentation and grading tool is developed to facilitate the construction of ORIGA(-light). A quantified objective benchmarking method is proposed, focusing on optic disc and cup segmentation and Cup-to-Disc Ratio (CDR). Currently, ORIGA(-light) contains 650 retinal images annotated by trained professionals from Singapore Eye Research Institute. A wide collection of image signs, critical for glaucoma diagnosis, are annotated. We will update the system continuously with more clinical ground-truth images. ORIGA(-light) is available for online access upon request.
视网膜眼底图像是记录视网膜健康状况的一种重要方式,被广泛用于诊断青光眼、糖尿病视网膜病变和年龄相关性黄斑变性等眼部疾病。然而,如今获取的大量视网膜数据大多存储在本地,其中宝贵的嵌入式临床知识并未得到有效利用。在本文中,我们介绍了一个在线存储库ORIGA(-light),其旨在与公众共享临床真实视网膜图像;为研究人员提供开放访问权限,以便他们对自己的计算机辅助分割算法进行基准测试。我们开发了一个内部图像分割和分级工具,以促进ORIGA(-light)的构建。提出了一种量化的客观基准测试方法,重点关注视盘和视杯分割以及杯盘比(CDR)。目前,ORIGA(-light)包含650张由新加坡眼科研究所训练有素的专业人员标注的视网膜图像。对青光眼诊断至关重要的各种图像特征都进行了标注。我们将用更多的临床真实图像不断更新该系统。ORIGA(-light)可应要求在线访问。