Automated diabetic retinopathy screening system

自动化糖尿病视网膜病变筛查系统

• 批准号: 7792138
• 负责人: Peter N Soliz
• 金额: $ 25万
• 依托单位: VISIONQUEST BIOMEDICAL, LLC
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2010-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7792138
• 关键词: Algorithms; Aneurysm; Applications Grants; Area; Automation; Blindness; Characteristics; Clinic; Clinical; Color; Community Healthcare; Computer Assisted; Computer-Assisted Diagnosis; Computers; Data Set; Detection; Development; Diabetes Mellitus; Diabetic Retinopathy; Diagnosis; Doctor of Philosophy; Early Diagnosis; Ensure; Environment; Exudate; Eye; Foundations; Goals; Health Personnel; Health Sciences; Health Services Accessibility; Healthcare; Hemorrhage; Human; Image; Image Compression; Individual; Institutes; Institution; Iowa; Lead; Lesion; Life; Mammography; Medical; Medical center; Modality; Online Systems; Ophthalmic examination and evaluation; Ophthalmologist; Ophthalmology; Ophthalmoscopes; Pap smear; Peer Review; Performance; Phase; Physician Executives; Population; Populations at Risk; Private Practice; Process; Productivity; Publications; Quality of life; Reader; Reading; Research; Research Infrastructure; Research Personnel; Resolution; Retina; Retinal; Retinal Diseases; Screening procedure; Sensitivity and Specificity; Services; Site; Solutions; South Texas; Specialist; Staging; Support System; System; Techniques; Technology; Telemedicine; Testing; Texas; Universities; Variant; Vision; Western World; base; clinically significant; diabetic; digital; experience; image processing; improved; macular edema; meetings; neovascularization; novel strategies; outreach; outreach program; performance tests; programs; prototype; public health relevance; vision science

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.

描述（由申请人提供）：该拟议项目的动机是，如果不引入计算机辅助的视网膜图像诊断，对糖尿病患者进行全面、大规模的视网膜病变筛查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，其中不到一半的人定期接受糖尿病视网膜病变筛查。 缺乏医疗保险和医疗保健提供者的获取给近 1000 万糖尿病患者带来了重大障碍。 创建一种负担得起且易于使用的解决方案来为这些糖尿病患者提供筛查服务对医疗保健界来说是一项重大挑战。 利用人类“阅读器”对每个病例​​进行评分的针对美国公民的全面筛查计划将非常昂贵。 解决方案是实施类似于其他医疗应用的计算机辅助技术，例如乳房X光检查和子宫颈抹片检查；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，每种算法仅检测一种特定类型的病变，例如深色病变、白色病变或血管特征。这些算法已经使用单一模式（像素格式、SLO、标准眼底镜、彩色、无红色等）进行了测试，并且每个新相机都可能需要对算法进行大量重新调整。该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方法。 这项研究的意义有两方面。首先，通过提高阅读中心的生产力，更多的高危糖尿病患者将能够获得这项服务，从而通过早期发现和治疗来提高生活质量。其次，通过提供经过验证的、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效率提高而获得经济利益。我们的系统不会取代当前的人类读者；它只是允许将病例的吞吐量增加五倍或更多，而不会牺牲敏感性和特异性。 公共健康相关性：如今，大约有 1000 万糖尿病患者没有接受年度眼科检查。如果没有这些检查，就不可能及早发现威胁视力的视网膜病变。由此导致的许多糖尿病患者早期视力丧失是西方世界失明的主要原因。 没有足够的医疗专家来为这一人群进行眼科检查。 如果没有基于计算机的筛查，就不可能对人群进行大规模筛查。