AUTOMATIC ANALYSIS OF 3-D AND 4-D RADIOLOGICAL IMAGES

描述：（改编自申请人摘要）许多放射成像 现在存在产生三维（3-D）和四维（4-D）的模态， 解剖结构的三维（4-D）图像。 不幸的是， 对这些数据集进行分析和测量仍然很麻烦。 简化3D/4D图像的分析对于能够 评估3-D/4-D成像模式的长期效用。 这项建议 解决这个普遍问题。 据信，自动分析 系统，由操作员提供的线索的协助下，可以更彻底，更 准确地，更有效地从一个 3-D/4-D放射图像比纯手动技术。 申请人提出设计交互式自动化3-D/4-D 放射图像分析系统，操作员可以通过该系统定义许多 通过柔性显示器的图标和象征性问题线索类型 接口的线索进入一个面向对象的模型， 交互式动态场景模型。 利用问题信息 存储在IDS模型中，自动场景分析（阿萨）引擎提取 所需的解剖区域。 阿萨引擎使用多阶段分析 利用器官形态学、几何学（基于形状）和 功能特性;它还使用全局拓扑 （器官对器官）限制。 这个项目的早期重点是设计算法， 阿萨引擎和IDS模型。 随着方法的成熟，申请人建议 构建系统的工作原型。 将进行验证 （1）在整个过程中，将重点放在四个应用程序： 3-D/4-D X线计算机断层扫描的心内膜和心外膜边界 (CT)图像;（2）分析真实的3-D血管造影片;（3）提取和 三维磁共振成像（MRI）中的上气道分析 （4）先天性心脏病的MRI三维图像分析。 虽然算法正在设计中，验证测试，涉及一个小的 数据的子集，将被完成以建立算法功能。 后来，随着算法的成熟，详细的测试，使用更大的序列， 数据，将做定量比较自动生成 手动生成的结果。

DESCRIPTION: (Adapted from Applicant's Abstract) Many radiological imaging modalities now exist that generate three-dimensional (3-D) and four dimensional (4-D) images of the anatomy. Unfortunately, techniques for analyzing and making measurements on such data sets remain cumbersome. Simplying the analysis of 3-D/4-D images is critical to being able to assess the long-term utility of 3-D/4-D imaging modalities. This proposal addresses this general issue. It is believed that an automated analysis system, assisted by operator-supplied cues, can more thoroughly, more accurately, and more efficiently extract anatomical information from a 3-D/4-D radiological image than purely manual techniques. The applicants propose to devise an interactive automated 3-D/4-D radiological image analysis system by which the operator can define many types of iconic and symbolic problem cues through a flexible display interface with the cues going into an object-oriented model, the interactive dynamic scene (IDS) model. Drawing on the problem information stored in the IDS model, an automatic scene-analysis (ASA) engine extracts the desired anatomical regions. The ASA engine uses a multi-stage analysis procedure that exploits organ morphological, geometrical (shape-based), and functional characteristics; it also uses global topological (organ-to-organ) constraints. The early emphasis of this project is on devising the algorithms for the ASA engine and IDS model. As methods mature, the applicants propose to construct a working prototype of the system. Validation would be done throughout and would focus on four applications: (1) extraction of the endocardial and epicardial borders from 3-D/4-D X-ray computed tomography (CT) images; (2) analysis of true 3-D angiograms; (3) extraction and analysis of the upper airway in 3-D Magnetic Resonance Imaging (MRI) images; and (4) analysis of congenital heart defects in 3-D MRI images. While algorithms are being devised, validation tests, involving a small subset of data, would be done to establish the algorithm functionality. Later, as algorithms mature, detailed tests, using larger sequences of data, would be done to quantitatively compare automatically generated results to manually generated results.