Retinal Vessel Measurement and Characterization System

视网膜血管测量和表征系统

• 批准号: 6693993
• 负责人: MARK P WILSON
• 金额: $ 10.58万
• 依托单位: KESTREL CORPORATION
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-08-01 至 2004-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6693993
• 关键词: artery; clinical research; digital imaging; human data; measurement; retina circulation disorder; technology /technique development; veins

DESCRIPTION (provided by applicant): Retinal microvascular abnormalities are related to many ocular and systemic diseases including diabetic retinopathy, hypertension, stroke, and cerebral micro-vascular diseases. For example generalized arteriolar narrowing and arteriovenous nicking appear to be irreversible long-term markers of hypertension. Findings suggest that retinal photography may be useful for assessing risk stratification and screening for retinal disease in appropriate populations. Highly evolved imaging solutions and computer processing power have opened a door to quantify these abnormalities. A methodology is suggested that is efficient and comprehensive because of computer automation, that is repeatable, free of inter- and intra-reader variability, precise, and consistent with the human analysts' techniques. We propose to develop and validate a system that extracts retinal vessels, classifies their bifurcations and crossings, and quantifies a diameter measurement of the retinal vas-culature system. The Auto-Cal system will use advanced morphological and Gaussian filtering techniques to segment the vessel network. Once segmented the crossings and bifurcations will be classified through morphological skeletonization path traversing and pruning algorithms. The vessel diameter is then calculated by fitting the gray level profile to Gaussian parameters that describe a typical vessel. The system will be tested on 50 digital images, which will have their 8 major vessels manually measured with a previously developed computer-aided tool. High statistical correlation with manually derived vessel diameters will determine the success of the process. The specific Phase I aims are to 1) Develop and validate a fully automatic retinal vessel extraction algorithm to segment the arteries and veins from a digital fundus photograph, 2) Develop and validate a vessel bifurcation and crossing recognition algorithm, and 3) Develop and validate a vessel diameter measurement algorithm. In Phase II the Auto-Cal tool will be used in a comparative study to examine 400 pre-proliferative diabetic retinopathy patients. The vessels have been manually measured. These data will be used to validate the system against a large "ground truth" population.

描述（申请人提供）：视网膜微血管异常与许多眼部和全身疾病相关，包括糖尿病视网膜病变、高血压、中风和脑微血管疾病。例如，广泛的小动脉狭窄和动静脉缺口似乎是高血压的不可逆的长期标志。研究结果表明，视网膜摄影可能有助于评估适当人群的风险分层和筛查视网膜疾病。高度发展的成像解决方案和计算机处理能力为量化这些异常打开了大门。 由于计算机自动化，建议采用一种有效且全面的方法，该方法是可重复的，没有读者之间和读者内部的可变性，精确且与人类分析人员的技术一致。我们建议开发和验证一个系统，该系统可以提取视网膜血管，对其分叉和交叉进行分类，并量化视网膜血管系统的直径测量。 Auto-Cal 系统将使用先进的形态学和高斯过滤技术来分割血管网络。一旦分割，交叉点和分叉点将通过形态骨架化路径遍历和修剪算法进行分类。然后通过将灰度轮廓拟合到描述典型血管的高斯参数来计算血管直径。该系统将在 50 张数字图像上进行测试，其中 8 艘主要船只将使用先前开发的计算机辅助工具进行手动测量。与手动得出的血管直径的高度统计相关性将决定该过程的成功。 第一阶段的具体目标是 1) 开发和验证全自动视网膜血管提取算法，以从数字眼底照片中分割动脉和静脉，2) 开发和验证血管分叉和交叉识别算法，以及 3) 开发和验证血管直径测量算法。 在第二阶段，Auto-Cal 工具将用于一项比较研究，以检查 400 名增殖前糖尿病视网膜病变患者。这些船只已被手动测量。这些数据将用于针对大量“真实情况”群体验证系统。