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，我们提出了Eyeart，这是一种具有高诊断症状的自动糖尿病性视网膜病变（DR）筛查的视网膜图像分析工具。 Eyeart凭借其与Eyepacs的界面，无许可，可扩展的远程医疗平台，将有助于扩大DR筛查，并有助于弥合糖尿病患者数量和眼保健提供者的数量之间成倍增长的差异。研究表明，从遗传上讲，拉丁裔人口易于发展糖尿病。他们因糖尿病性视网膜病而导致的视力丧失的脆弱性进一步加剧了诸如无法获得眼科临床医生，缺乏保险和缺乏教育的因素。根据洛杉矶县卫生服务部（DHS）的说法，糖尿病患者的情况尤其严峻，目前的等待时间超过6-9个月，用于视网膜病变检查的视网膜检查。这可以导致治疗延迟和向不可逆转的视力丧失发展。为了减少这种糖尿病人群中视力丧失的风险，我们建议将高级图像分析算法与现有的远程医疗计划结合使用，以更快地筛查，允许对眼科医生的任命重新审核，并帮助高危患者的三叶叶。我们的I阶段原型自动DR筛选工具已经通过在大型公共视网膜数据集上击败当前的学术和商业DR筛查表现出巨大的潜力。展望未来，我们将以我们的方法为基础，并进一步开发创新的，定制的算法，以用于关键的低级图像处理步骤，同时利用计算机视觉的最新进展以及用于高级，推理的机器学习领域，以生成临床等级DR筛选工具。我们的病变本地化和筛查引擎将与Eyepacs在功能上集成，以进一步推动筛查的扩展，特别是受益于资源不足的筛查计划，例如LAC-DHS安全网及其大型西班牙裔糖尿病人群。