AUTOMATED IMAGE REGISTRATION FOR CLINICAL NEUROIMAGING

我们建议的基本假设是，图像配准可以常规地应用于临床领域，以改进特定神经疾病的诊断和管理。这项提议的长期目标是开发一种完全自动化的系统，用于计算机轴位断层扫描(CT)的扫描配准。最近完成的工程研究表明，所有注册步骤都可以在2分钟内完成。第一阶段的具体目标是：1)创建一个可以在实验室环境中使用的工程原型系统，以确认工程研究的有效性。2)评价CT扫描三种特定医学指征(使用和不使用造影剂)的速度、方便性和准确性。工程原型包括：a)用于接收和解码CT数据的软件，b)特定于研究的前后处理模块，c)注册引擎，以及d)可视化工具。第一阶段的研究将在医院实验室提供明确的原理和物理测试演示。这些信息将用于第二阶段，以设计一种商业强度的产品，在急诊室和临床环境中进行测试，从而符合FDA的指南。拟议的商业应用：尽管图像配准有可能改善神经科患者的诊断和管理，但由于与手动处理相关的成本和时间，图像配准不能广泛应用。自动化将降低成本。在中风病和脑肿瘤的诊断和治疗中的应用是该技术的关键应用。

The basic hypothesis of our proposal is that image registration can be routinely applied in the clinical domain to improve diagnosis and management of specific neurological disorders. The long term goal of this proposal is the development of a completely automated system for registration of scans from computed axial tomography (CT). Recently completed engineering studies suggest that all registration steps can be performed within 2 min. The specific aims for Phase I are: 1) To create an engineering prototype system that can be used in a laboratory environment to confirm the validity of the engineering study. 2) To evaluate the speed, convenience and accuracy of the prototype on three specific medical indications for CT scanning (with and without contrast media.) The engineering prototype includes: a) software to receive and decode CT data, b)study-specific pre- and post-processing modules, c) a registration engine, and d) visualization tools. Phase I research will provide explicit demonstration of principle and physical testing in a hospital laboratory. This information will be used in Phase II to design a commercial strength product with testing in the emergency room and clinical environments leading toward compliance with FDA guidelines. PROPOSED COMMERCIAL APPLICATIONS: Despite the potential for improving diagnosis and management of neurological patients, image registration cannot be applied widely because of the cost and time associated with manual processing. Automation will lower the cost. Application to diagnosis and management of stroke disease and brain tumors are key application of this technology.