BIOMEDICAL IMAGE PROCESSING

生物医学图像处理

• 批准号: 3774952
• 负责人: B L TRUS
• 金额: --
• 依托单位: CENTER FOR INFORMATION TECHNOLOGY
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/3774952
• 关键词: artery; biomedical automation; blood flow measurement; cataract; clinical biomedical equipment; computer simulation; computer system hardware; image processing; imaging /visualization /scanning; lens; mathematical model; noninvasive diagnosis; ultrasound blood flow measurement

This project uses sophisticated image processing techniques to analyze biomedical images. The goal is to establish collaborations with biomedical experts who require new algorithms and possibly new hardware capability to solve difficult imaging problems. Typically, complex new mathematical algorithms as well as new combinations of existing algorithms are utilized. We attempt to integrate the best computer platform for each problem with the desired goal of the project, using such diverse computers as an Apple MacIntosh, a DEC VAX or Alpha, a SUN workstation, or an Intel iPSC/860 supercomputer. Two current projects include ophthalmic image acquisition and analysis and ultrasound image analysis. In the first project, research has been ongoing between the National Eye Institute (NEI) and DCRT in the area of computerizing instrumentation and the automatic analysis of anterior eye segment images. The goal in development of computer-based NEI instrumentation is two fold: (a) to provide accurate and reproducible numerical information (b) to develop image analysis in a user-friendly and systematic way. This year we devised algorithms for the analysis of retroillumination images (frontal plane lens images). This includes methods of segmentation as well as several unique algorithms for calculating the centrality and integrated density of the cataract under study. We have begun to document these procedures. A second major collaborative effort with NHLBI as well as with DCRT/DSB is the measuring of blood flow velocity in arteries, and possibly through heart valves, non-invasively. Current ultrasound technology allows physicians to view flow approximately, but not quantitatively. Present systems provide a color display of flow which is actually a simulation of flow velocity. The goal for this project is to use an echo Dippler color mapping system and image the same artery or organ from multiple locations and orientations, then to sue 3D calculations and reconstruct a true flow profile. The method being developed should allow not only better calculation of velocity profiles, flow volume and resistances, but also estimations of pressures across valve orifices and stenotic arteries and for other purposes. The correction of flow velocity values on a two- dimensional images was successfully implemented this year. However, the alignment of data into a 3D and 4D volume has encountered difficulties with the accuracy of the bird 3 space tracker, which may not have the resolution to track objects that are smaller in size then the sensing crystals.

这个项目使用复杂的图像处理技术来分析 生物医学图像 目标是与 生物医学专家需要新的算法和可能的新硬件 解决成像难题的能力。 通常，复杂的新 数学算法以及现有的 使用算法。 我们试图整合最好的计算机 平台为每个问题与项目的预期目标，使用 各种各样的电脑，如苹果麦金托什，DEC VAX或Alpha，SUN 工作站或Intel iPSC/860超级计算机。 目前的两个项目包括眼科图像采集和分析 和超声图像分析。 在第一个项目中， 国家眼科研究所（NEI）和DCRT之间正在进行的 计算机化仪器与眼前节自动分析 分割图像。 基于计算机的NEI的发展目标 仪器有两个方面：（a）提供准确和可再现的 数字信息（B），以用户友好的方式开发图像分析， 系统的方式。 今年我们设计了一种算法， 后向照明图像（额状面透镜图像）。 这包括 分割方法以及几种独特的算法， 计算白内障的中心性和积分密度， study. 我们已经开始记录这些程序。 与NHLBI以及DCRT/DSB的第二项主要合作努力 是测量动脉中的血流速度， 心脏瓣膜，非侵入性的 目前的超声波技术允许 医生可以近似地观察血流，但不能定量地观察。 本 系统提供实际上是模拟的流动的彩色显示 流速。 该项目的目标是使用回声多普勒 彩色映射系统和图像相同的动脉或器官从多个 位置和方向，然后进行3D计算并重建 一个真实的流动剖面。 正在开发的方法不仅可以让 更好地计算速度分布、流量和阻力， 还可以估计瓣膜口和狭窄动脉的压力 以及用于其他目的。 本文对两种不同流速下的流速值进行了修正， 三维图像在今年成功实施。 但 将数据对齐到3D和4D体积中遇到了困难 与准确的鸟3空间跟踪器，这可能没有 分辨率，以跟踪尺寸小于感测的物体 晶体