MEDICAL IMAGING SOFTWARE USING DISTRIBUTED OBJECTS

本研究的目标是开发一个开放的、可扩展的医疗 图像分析环境，允许快速原型制作，验证， 和医学成像算法的部署。 这种环境释放了 分析员不必处理低级编程问题。 等 一个环境将促进知识、数据和 算法以及提供协作群件功能 工作或诊断。 目前可用于图像分析的大多数软件系统是 过于笼统，不能提供医学图像支持，或者过于刚性 专注于具体的应用。 我们的软件环境将 专注于医学成像，我们将展示它的灵活性 用于开发各种复杂的成像应用， 图像分割、图像配准和计算机辅助 诊断. 我们的软件环境使用软件技术的最新进展， 分布式对象领域提供了一种行业标准方法 实现不同应用程序之间的无缝集成。 这项技术 还允许轻松的可定制性、可扩展性和跨平台 应用程序和互联网连接的兼容性。 这 环境集成了各种组件，包括对象 面向对象的第四代编程语言;一种完全可定制的 图形用户界面;数据库管理系统扩展 用于图像处理、统计和数学分析的库; 以及先进的可视化技术。 建议的商业应用 我们设想两种类型的用户为这个软件环境-（1） 医学成像研究人员或医学成像解决方案提供商，以及 (2)临床医生或临床研究人员。 第一类用户将是 能够完全自定义应用程序。 第二类用户 将该软件用于特定的应用程序。 我们的基石 这种环境的设计方法将允许快速 针对不同应用和不同类型的 用户.

The goal of this research is to develop an open and extensible medical image analysis environment which allows rapid prototyping, validation, and deployment of medical imaging algorithms. This environment frees the analyst from having to deal with low level programming issues. Such an environment would facilitate the sharing of knowledge, data and algoriths as well as providing groupware capabilities for collaborative work or diagnosis. Most software systems currently available for image analysis are either too general and do not provide medical image support, or are too rigid and focused on specific applications. Our software environment will concentrate on medical imaging and we will demonstrate it's flexibility for developing various sophisticated imaging applications encompassing the areas of image segmentation, image registration, and computer-aided diagnosis. Our software environment uses recent advances in software technology in the area of distributed objects to provide an industry-standard method for seamless integration between diverse applications. This technology also allows easy customizability, extensibility and cross-platform compatibility of an application and Internet connectivity. This environment integrates a variety of components including, an object oriented fourth generation programing language; a fully customizable Graphical User Interface; a database management system extensive libraries for image processing, statistical and mathematical analyses; and, advanced visualization. PROPOSED COMMERCIAL APPLICATION We envision two types of users for this software environment--(1) medical imaging researchers or medical imaging solution providers, and (2) clinicians or clinical researcher. The first type of users will be able to customize the application completely. The second type of users will use the software for specific applications. Our building-block approach to the design of this environment will allow rapid customization for different applications and for the different types of users.