Automated diabetic retinopathy screening system

描述(由申请人提供)：这项拟议的项目的动机是这样一个事实，即在没有引入计算机辅助诊断视网膜图像的情况下，全面、广泛地筛查糖尿病患者的视网膜病变在经济上是令人望而却步的。美国有超过2000万人患有糖尿病，据估计，这些人中只有不到一半的人定期接受糖尿病视网膜病变的筛查。缺乏医疗保险和医疗保健提供者给近1000万糖尿病患者带来了重大障碍。为这些糖尿病患者提供负担得起和可获得的解决方案，对医疗保健社区来说是一个巨大的挑战。为美国公民提供一项全面的筛查计划，利用人类的“阅读器”对每个病例进行分级，费用将高得令人望而却步。解决方案是实施一种类似于其他医疗应用程序的计算机辅助技术，如乳房X光检查和巴氏涂片；这将为我们的高危人群提供全面、定期的筛查。许多研究人员开发了特定的算法，每个算法只检测一种特定类型的病变，如黑色病变、白色病变或血管特征。这些算法已经使用单一通道(像素格式、SLO、标准眼底镜、彩色、无红色等)进行了测试。而且，每一台新相机都需要对算法进行重大调整。这个项目的目标是演示并验证一种全新的计算机辅助视网膜图像分级的方法。这项拟议的研究的意义是双重的。首先，通过提高阅读中心的生产率，更多的高危糖尿病患者将能够获得这项服务，通过早期发现和治疗来提高生活质量。其次，通过提供一个经过验证的、强大的计算机辅助评分系统，所有现有的阅读中心都将通过我们系统的额外效率从经济上受益。我们的系统不会取代目前的人类阅读器；它只是允许将案件吞吐量增加五倍或更多，而不牺牲敏感性和特异性。 与公共卫生相关：今天，约有1000万糖尿病患者不接受年度眼科检查。如果没有这些检查，早期发现威胁视力的视网膜病变是不可能的。由此导致的许多糖尿病患者早期失明是西方世界失明的主要原因。医疗保健专家的数量不足，无法为这一人群进行眼睛检查。如果没有基于计算机的筛查，就不可能进行大规模的人口筛查。

DESCRIPTION (provided by applicant): This proposed project is motivated by the fact that comprehensive, broad-scale screening of diabetics for retinopathy is economically prohibitive without the introduction of computer-assisted diagnosis of retinal images. Over 20 million people in the U.S. have diabetes and it is estimated that less than half of those individuals are screened periodically for diabetic retinopathy. Lack of medical coverage and access to healthcare providers imposes major obstacles for nearly 10 million diabetics. Creating an affordable and accessible solution to providing screening services to these diabetics presents a significant challenge to the healthcare community. A comprehensive screening program for U.S. citizens utilizing human "readers" to grade each case would be prohibitively expensive. The solution is to implement a computer-assisted technology similar to other medical applications, such as mammograms and Pap smears; that would provide comprehensive, periodic screening of our at-risk population. Numerous investigators have developed specific algorithms, each detecting only one specific type of lesion, such as dark lesions, white lesions, or vessel characteristics. These algorithms have been tested using a single modality (pixel format, SLO, standard funduscope, color, red free, etc.) and each new camera can require significant re-tuning of the algorithms. The goal of this project is to demonstrate and then validate an entirely new approach for computer-assisted grading of retinal images. The significance of this proposed research is two-fold. First, by increasing the productivity of reading centers, a much larger population of at-risk diabetics will have access to this service, leading to improved quality of life through early detection and treatment. Second, by providing a validated, robust computer-assisted grading system, all existing reading centers would benefit economically through the added efficiency of our system. Our system does not replace current human readers; it simply allows an increase of throughput of cases by factors of five or more without sacrificing sensitivity and specificity. PUBLIC HEALTH RELEVANCE: Today, about 10 million diabetics do not receive annual eye examinations. Without these examinations early detection of vision threatening retinopathy is not possible. The resulting early loss of vision for many of these diabetics is the leading cause of blindness in the western world. There is an insufficient number of healthcare specialists to perform eye examinations for this population. Without computer-based screening, a broad-scale screening of the population will not be possible.