IMPROVEMENT OF DIGITAL ANGIOGRAPHY OF CORONARY ARTERIES

冠状动脉数字血管造影术的改进

• 批准号: 3347902
• 负责人: JOHN M FITZPATRICK
• 金额: $ 21.42万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1986
• 资助国家: 美国
• 起止时间: 1986-07-01 至 1989-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3347902
• 关键词: angiography; arteriosclerosis; artery stenosis; artificial intelligence; clinical biomedical equipment; coronary artery; diagnosis procedure safety; heart disorder diagnosis; heart imaging /visualization /scanning; human subject; image processing

Coronary arteriosclerosis is a leading cause of death in U.S., and it is to a large degree the presence or absence of severe coronary stenoses which determines the risk of death. Because many patients who suffer from this disease are asymptomatic until their first attack, a safe, inexpensive diagnostic procedure for detecting coronary artery stenoses would be beneficial. The diagnosis as currently carried out requires that a large catheter be inserted into the orifice of each artery in order to inject opaque dye to make the arteries visible with X rays. The increased contrast sensitivity of digital subtraction angiography (DSA) permits a less invasive technique involving an injection into the aortic root, a smaller catheter, and reduced dye volumes, but it has been of only limited success largely because of image degradation caused by patient motion during image acquisition. The aim of this project is to develop and test image processing algorithms for the improvement of digital angiography of coronary arteries. The algorithms search for a geometrical transformation to produce an optimal registration of two images before subtraction. They are based on a new application of the fundamental principles of fluid dynamics, a new class of transformation functions, a new method of machine calibration, and new application of search methods developed in the field of artifical intelligence for function optimization. As a result these algorithms represent the first approach to image registration which is capable of handling true three dimensional warping. The development and evaluation of the algorithms will be carried out on both a specially designed phantom and on data derived in a new way from patient studies. The patient studies will be acquired during angioplasty procedures in which an inflated balloon and catheter will serve as phantom arteries of known dimensions. The availability of known phantoms located in the chest on a beating human heart will provide for the first time an opportunity for quantitative evaluation of the success of the image enhancement algorithms in a realistic environment. Thus, the proposed research will employ new techniques of image registration with a new technique for image evaluation to the problem of reducing motion effects in digital subtraction angiography.

冠状动脉硬化是美国的主要死因，并且应当 在很大程度上存在或不存在严重的冠状动脉狭窄， 决定了死亡的风险。 因为许多患有这种疾病的患者 疾病在第一次发作前是无症状的， 检测冠状动脉狭窄的诊断程序将是 有利于 目前进行的诊断需要大量的 将导管插入每个动脉的开口，以便注射 不透明的染料使动脉在X射线下可见。 增加的 数字减影血管造影（DSA）的对比敏感度允许 一种侵入性较小的技术，包括向主动脉根部注射， 更小的导管和减少的染料体积，但它一直是有限的 成功主要是因为患者运动引起的图像退化 在图像采集期间。 该项目的目的是开发和测试 数字血管造影图像处理算法的改进 冠状动脉 算法搜索几何变换 以在减影之前产生两个图像的最佳配准。 他们 基于流体基本原理的新应用 动力学，一类新的变换函数，一种新的机器方法 校准，以及该领域开发的搜索方法的新应用 用于功能优化的人工智能。 因此这些 算法代表了图像配准的第一种方法， 能够处理真正的三维翘曲。 发展和 算法的评估将在两个特定的平台上进行， 设计的体模，并以新的方式从患者研究中获得的数据。 患者研究将在血管成形术期间采集，其中 膨胀的气囊和导管将用作已知的 尺寸. 位于胸部的已知幻影的可用性 跳动的人类心脏将首次提供机会 图像增强算法成功与否的定量评价 在现实的环境中。 因此，拟议的研究将采用新的 图像配准技术与图像评价新技术 涉及在数字减影中减少运动效应的问题 动脉造影