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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

基本信息

批准号：
8466969
负责人：
Kaushal Solanki
金额：
$ 19.95万
依托单位：
EYENUK, INC.
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-05-08 至 2014-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8466969
关键词：
Address Agreement Algorithms Appointment Architecture Area Arts Awareness Blindness California Car Phone Clinic Clinical Code Complications of Diabetes Mellitus Computer Vision Systems Computer software Consult County Detection Diabetes Mellitus Diabetic Retinopathy Dictionary Disadvantaged Economic Factors Ensure Exudate Eye Faculty Feedback Goals Gold Health Healthcare Hemorrhage Hispanics Human Image Image Analysis Incidence Institutes Insurance Coverage Internet Joints Latino Lesion Localized Lesion Location Los Angeles Machine Learning Measures Medical center Microaneurysm Online Systems Ophthalmologist Optometry Patient Education Patients Phase Plug-in Population Populations at Risk Primary Health Care Principal Investigator Process ROC Curve Reading Reproducibility Research Research Infrastructure Research Project Grants Retinal Diseases Risk Rural Rural Health Sensitivity and Specificity Severities Side Small Business Innovation Research Grant Software Design Software Engineering Software Tools Statistical Computing System Telemedicine Testing Time Universities Work abstracting base bioimaging computerized data processing cost cotton wool spots diabetes risk experience image processing neovascularization prevent prototype public health relevance screening socioeconomics success tool tv watching user-friendly web interface

项目摘要

DESCRIPTION (provided by applicant): Abstract In this small business innovations research (SBIR) project, we present aiArt: Advanced Image Analysis Tools for Diabetic Retinopathy Telemedicine applications. aiArt (pronounced eye-art), with its automated image analysis tools and user-friendly telemedicine web-interface, will enable exponential expansion of diabetic retinopathy screenings, thus fulfilling a significant health need as the number of people with diabetes climbs over the years. Latino population is genetically more prone to diabetes. Factors such as lack of awareness, lack of insurance coverage, and lack of access to expert clinicians greatly increase this disparity population's vulnerability to blindness due to DR. The situation is particularly grim in Los Angeles County, where there is a backlog of several thousand patients waiting to see an ophthalmologist, causing very long appointment wait times (often over six months). To help reduce risk of vision loss in this population, we propose to use advanced image analysis algorithms in conjunction with existing telemedicine initiatives to enable faster screening, allow reprioritization of ophthalmologist appointments, and to provide patient education tools. Our automated image analysis algorithms represent cutting-edge of research in image processing, computer vision, and machine learning. The analysis engine will be closely integrated with simple, easy-to-use web-based telemedicine infrastructure provided by an existing, popular, telemedicine initiative, EyePACS.

描述（由申请人提供）：摘要在这个小企业创新研究（SBIR）项目中，我们提出了aiArt：糖尿病视网膜病变远程医疗应用的高级图像分析工具。aiArt（发音为eye-art）凭借其自动化图像分析工具和用户友好的远程医疗网络界面，将使糖尿病视网膜病变筛查呈指数级增长，从而满足随着糖尿病患者人数逐年攀升的重大健康需求。拉丁裔人口在遗传上更容易患糖尿病。缺乏认识、缺乏保险覆盖以及缺乏专家临床医生等因素大大增加了这一差距，使人口容易因DR而失明。尤其是在洛杉矶县，那里有几千名病人等待看眼科医生，导致预约等待时间很长（通常超过六个月）。为了帮助降低这一人群视力丧失的风险，我们建议使用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，允许眼科医生预约的重新优先级，并提供患者教育工具。我们的自动图像分析算法代表了图像处理、计算机视觉和机器学习领域的前沿研究。分析引擎将与现有的流行远程医疗倡议EyePACS提供的简单易用的基于网络的远程医疗基础设施紧密结合。