Advanced Image Analysis Tools for Diabetic Retinopathy Telemedicine Applications

用于糖尿病视网膜病变远程医疗应用的高级图像分析工具

• 批准号: 8891422
• 负责人: Kaushal Solanki
• 金额: $ 39.42万
• 依托单位: EYENUK, INC.
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-05-08 至 2016-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8891422
• 关键词: Adult; Age; Agreement; Algorithms; Appointment; Area; Background Diabetic Retinopathy; Blindness; California; Caring; Clinic; Clinical; Clinical effectiveness; Color; Complications of Diabetes Mellitus; Computer Vision Systems; Consult; County; Data; Data Set; Descriptor; Detection; Development; Diabetes Mellitus; Diabetic Retinopathy; Diagnostic; Dimensions; Economic Factors; Economically Deprived Population; Education; Engineering; Evaluation; Eye; Faculty; Fundus; Goals; Gold; Health; Health Services; Hispanics; Image; Image Analysis; Industry; Institutes; Insurance; International; Latino; Lead; Learning; Lesion; Licensing; Los Angeles; Machine Learning; Marketing; Measures; Ophthalmologist; Ophthalmology; Optometry; Patient Triage; Patients; Pattern Recognition; Phase; Population; Predictive Value; Primary Health Care; Process; Protocols documentation; Provider; ROC Curve; Reader; Receiver Operating Characteristics; Reporting; Research; Research Project Grants; Resolution; Retinal; Retinal Diseases; Risk; Sensitivity and Specificity; Severities; Small Business Innovation Research Grant; Small Business Technology Transfer Research; Software Engineering; Software Tools; Surveys; System; Telemedicine; Testing; Texture; Time; Training; Triage; Universities; Validation; Work; base; bioimaging; clinical care; cloud based; computerized; cost; design; diabetic; diabetic patient; experience; high risk; image processing; innovation; prevent; programs; prototype; safety net; screening; socioeconomics; success; tool; usability

DESCRIPTION (provided by applicant): In this small business innovations research (SBIR) project we present EyeArt, a retinal image analysis tool for automated diabetic retinopathy (DR) screenings with high diag- nostic efficacy. With its interface to EyePACS, a license-free, scalable telemedicine plat- form, EyeArt will aid the expansion of DR screening and help bridge the exponentially growing disparity between the number of diabetic patients and the number of eye-care providers. Research suggests that the Latino population in general are genetically predisposed to develop diabetes. Their vulnerability to vision loss due to diabetic retinopathy is further compounded by factors such as lack of access to ophthalmology clinicians, lack of insurance, and lack of education. According to the Department of Health Services (DHS) in Los Angeles County (LAC) the situation for diabetics is particularly grim, with current wait times upwards of 6-9 months for retinal examinations for retinopathy screening. This can lead to treatment delays and progression towards irreversible vision loss. To help reduce risk of vision loss in this diabetic population, we propose to use advanced image analysis algorithms in conjunction with existing telemedicine initiatives to enable faster screening, allow reprioritizatin of ophthalmologist appointments, and aid in triage of high-risk patients. Our phase I prototype automatic DR screening tool has already shown great potential by beating current academic and commercial DR screening ap- proaches on large public retinal datasets. Going forward, we will build on our approach and further develop innovative, customized algorithms for critical low-level image processing steps, while leveraging on recent advances in computer vision, and machine learning areas for high-level, inference steps to produce a clinical grade DR screening tool. Our lesion localization and screening engine will be functionally integrated with EyePACS to further drive the expansion of screening, particularly benefiting under- resourced screening programs like the LAC-DHS safety net and its large Hispanic diabetic population.

描述（由申请人提供）：在这个小型企业创新研究（SBIR）项目中，我们展示了EyeArt，一个用于糖尿病视网膜病变（DR）自动筛查的视网膜图像分析工具，具有很高的诊断效率。EyeArt与EyePACS（一个免许可、可扩展的远程医疗平台）的接口将有助于扩大DR筛查，并帮助弥合糖尿病患者和眼科护理提供者数量之间呈指数增长的差距。研究表明，拉丁裔人口总体上在遗传上易患糖尿病。由于缺乏接触眼科医生的机会、缺乏保险和缺乏教育等因素，他们容易因糖尿病视网膜病变而导致视力丧失。根据洛杉矶县（LAC）卫生服务部（DHS）的数据，糖尿病患者的情况尤其严峻，目前为视网膜病变筛查进行视网膜检查的等待时间超过6-9个月。这可能导致治疗延迟，并发展为不可逆转的视力丧失。为了帮助降低糖尿病人群视力丧失的风险，我们建议将先进的图像分析算法与现有的远程医疗计划相结合，以实现更快的筛查，重新确定眼科医生预约的优先级，并帮助对高风险患者进行分诊。我们的第一阶段原型自动DR筛选工具已经在大型公共视网膜数据集上击败了目前的学术和商业DR筛选方法，显示出了巨大的潜力。展望未来，我们将以我们的方法为基础，进一步开发创新的定制算法，用于关键的低级图像处理步骤，同时利用计算机视觉和机器学习领域的最新进展，用于高级推理步骤，以生产临床级DR筛选工具。我们的病变定位和筛查引擎将与EyePACS功能集成，进一步推动筛查的扩展，特别是有利于资源不足的筛查项目，如LAC-DHS安全网及其庞大的西班牙裔糖尿病人群。