Efficient Interpretation of 3D Vascular Image Data

3D 血管图像数据的高效解读

• 批准号: 6684093
• 负责人: SANDY A. NAPEL
• 金额: $ 51.78万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-12-15 至 2005-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6684093
• 关键词: aneurysm; angiography; bioimaging /biomedical imaging; blood vessel occlusion; cardiovascular disorder diagnosis; computed axial tomography; computer assisted diagnosis; computer program /software; computer system design /evaluation; diagnosis quality /standard; human data; image processing; patient oriented research

DESCRIPTION (Provided by Applicant): Recent developments in Computed Tomography have resulted in the capability to image blood vessels in three dimensions and less invasively than conventional angiography. However, these developments have also resulted in the potential to generate thousands of images per patient study for radiological interpretation. As a result, it has become increasingly difficult to read each image separately and to reach an accurate diagnosis in a reasonable amount of time. Therefore, we propose to develop and validate technology that changes radiological interpretation of volumetric CT vascular image data from visual inspection of individual cross-sections to a paradigm that combines highly efficient, ergonomic, and interactive volumetric visualization and quantitative analysis. To this end, over the first three years of this project, we will develop a system of hardware and software specifically designed for this task. It will consist of a large-area high-resolution display, a set of human-computer interfaces specifically designed for facilitating interaction with large volumetric vascular data sets, and intelligent software capable of guiding the required interactions and generating blood-vessel-specific visualizations and quantitative results with minimal effort. We will conduct a clinical pilot study in the fourth year of the proposed work, during which radiologists will compare the use of a prototype system with conventional image-by-image reading for accuracy and efficiency. We will focus our analyses on (1) aortoiliac aneurysm, and (2) lower extremity occlusive disease, as test cases for the new technology. Upon completion of these studies, we expect that our developments will be easily adaptable to other applications both within and outside of vascular imaging, as well as to other imaging modalities such as MRI. Our overall goal is to change and validate the way crosssectional images are interpreted in general, thus resulting in improved accuracy and efficiency in the assessment of increasingly large volumes of medical image data.

描述（由申请人提供）：计算机断层扫描的最新发展 已经能够对血管进行三维成像 与传统血管造影相比，侵入性更小。然而，这些发展已经 还可以为每个患者生成数千张图像 放射学解释研究。结果，它变得越来越 很难单独读取每张图像并做出准确的诊断 合理的时间。因此，我们建议开发并验证 改变体积 CT 血管放射学解释的技术 从各个横截面的目视检查到范例的图像数据 结合了高效、符合人体工程学和交互式体积测量 可视化和定量分析。为此，前三 在这个项目的几年里，我们将开发一个硬件和软件系统 专门为此任务而设计的。它将由一个大面积的 高分辨率显示，一套专门的人机界面 旨在促进与大体积血管数据集的交互， 以及能够指导所需交互的智能软件 生成血管特定的可视化和定量结果 最小的努力。我们将在第四年进行临床试点研究 拟议的工作，在此期间放射科医生将比较 原型系统具有传统的逐图像读取的准确性和 效率。我们将重点分析 (1) 主髂动脉瘤，以及 (2) 下肢闭塞性疾病，作为新技术的测试案例。之上 完成这些研究后，我们预计我们的发展将很容易 适用于血管成像内外的其他应用，如 以及其他成像方式，例如 MRI。我们的总体目标是改变 并验证横截面图像的一般解释方式，从而 从而提高评估的准确性和效率 海量医学图像数据。