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）：该提议的项目是由以下事实激发的：对于视网膜病变的全面，广泛的糖尿病患者糖尿病患者的糖尿病患者在经济上是过时的，而无需对视网膜图像进行计算机辅助诊断。 在美国，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会因糖尿病性视网膜病的定期筛查。 缺乏医疗保险和获得医疗保健提供者的机会，对近1000万个糖尿病患者施加了主要障碍。 为这些糖尿病患者提供筛查服务的负担得起且易于使用的解决方案给医疗保健社区带来了重大挑战。 使用人类“读者”对每种情况进行评分的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学应用的计算机辅助技术，例如乳房X线照片和子宫颈抹片检查；这将为我们的高危人口提供全面的周期性筛查。 许多研究人员已经开发了特定的算法，每种算法仅检测一种特定类型的病变，例如黑暗病变，白色病变或血管特征。这些算法已经使用单个模态（像素格式，SLO，标准底尺，颜色，红色免费等）进行了测试，并且每个新相机都需要重新调整算法。该项目的目的是证明并验证一种全新的视网膜图像评分分级的方法。 这项拟议的研究的意义是两倍。首先，通过提高阅读中心的生产率，高危处的糖尿病人群将可以使用这项服务，从而通过早期检测和治疗来改善生活质量。其次，通过提供经过验证的，可靠的计算机辅助分级系统，所有现有的阅读中心都将通过我们系统的提高效率在经济上受益。我们的系统不能取代当前的人类读者；它只是允许通过五个或更多的因素增加案例的吞吐量，而不会牺牲灵敏度和特异性。 公共卫生相关性：今天，大约1000万糖尿病患者未接受年度眼科检查。如果没有这些检查，就不可能尽早发现视网膜病变。许多这些糖尿病患者的早期视力丧失是西方世界失明的主要原因。 对于该人群进行眼科检查的医疗专家数量不足。 如果没有基于计算机的筛查，就无法对人口进行广泛的筛查。