BIOMEDICAL IMAGE PROCESSING

该项目使用复杂的图像处理技术来分析 生物医学图像。我们的目标是与 需要新算法、可能还需要新硬件的生物医学专家 能够解决困难的成像问题。通常，复杂的新 数学算法以及现有的 利用了各种算法。我们试图集成最好的计算机 针对每个问题的平台，以及项目的预期目标，使用 种类繁多的计算机，如Apple MacIntosh、DEC VAX或Alpha、Sun 工作站或Intel iPSC/860超级计算机。 目前有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，研究一直在进行 国家眼科研究所(NEI)和DCRT在以下领域正在进行 计算机化仪器与前眼自动分析 分割图像。基于计算机的网络信息系统的发展目标 仪器有两个方面：(A)提供准确和可重现的 数字信息(B)在用户友好的情况下开发图像分析 和系统化的方式。今年，我们设计了算法来分析 逆照像(前平面透镜图像)。这包括 分割的方法以及几种独特的分割算法 计算白内障的中心度和综合密度 学习。我们已经开始记录这些程序。 与NHLBI以及DCRT/DSB的第二个主要协作工作 是测量动脉中的血流速度，并可能通过 心脏瓣膜，非侵入性。目前的超声波技术允许 医生只能粗略地观察血流，但不能定量观察。现在时 系统提供了实际上是模拟的流动的彩色显示 流速的大小。这个项目的目标是使用一个回声转发器 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，然后起诉3D计算和重建 真实的流动剖面。正在开发的方法不仅应该允许 更好地计算速度剖面、流量和阻力，但 同时估计瓣口和狭窄动脉的压力。 以及用于其他目的。两相流流速值的修正 维度图像在今年成功实施。然而， 将数据对齐到3D和4D卷遇到了困难 拥有鸟3号空间跟踪器的精确度，它可能没有 用于跟踪尺寸小于感测的对象的分辨率 水晶。

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.