Deployment Framework for Medical Imaging Applications

描述（由申请人提供）：有很多原因，相对 先进的医学图像处理方法扩散缓慢， 一个重要的原因是目前提供访问的模式：大多数 应用程序仍然依赖于专有软件和硬件环境 这会带来巨大的前期成本。 这项工作的最终目的是利用商品计算技术 开发一个开放的、可扩展的框架，用于部署医学图像处理 在当今的异构网络计算环境中， 该框架将为临床医生和研究人员提供访问 最先进的图像处理应用，而不管它们的特定 计算平台或连接它们的本地可用计算资源 联合数据库资源、高端计算资源，甚至 与他们的同事在一个点对点的计算环境中。 该项目第一阶段的目标是： (1)演示框架提供了对图像处理的访问 在很大程度上独立于本地计算的应用程序 资源 (2)证明框架是通用的，因为相同的组件可以 可重复用于部署各种各样的医学成像应用。 (3)证明框架可由第三方 允许高级用户创建和部署新的 应用. 第二阶段的工作将扩展框架，并发展两个示范项目， 应用-用于乳房X线摄影和多模态的计算机辅助诊断（CAD） 图像融合最终目标是获得关键的合作伙伴关系和私人 商业化所需的股权投资，将通过 推出创收版本的CAD和图像融合应用程序。

DESCRIPTION (provided by applicant): There are many reasons for the relatively slow proliferation of advanced medical image processing methods but a significant reason is the present paradigm for providing access: most applications are still tied to proprietary software and hardware environments that carry significant up-front costs. The ultimate intent of this work is leverage commodity computing technologies to develop an open, extensible framework for deploying medical image processing applications in the heterogeneous, networked computing environment of today. The framework will provide clinicians and researchers access to state-of-the-art image processing applications regardless of their particular computing platform or locally available computing resources connecting them with federated database resources, with high-end computing resources, or even with their colleagues in a peer-to-peer computing environment. The aims for Phase I of this project are: (1) Demonstrate that the framework provides access to image processing applications to an extent that is largely independent of local computing resources. (2) Demonstrate that the framework is general in that the same components can be reused for deploying a wide variety of medical imaging applications. (3) Demonstrate that the framework is customizable both by third-party developers and by end-users allowing power-users to both create and deploy new applications. Work in Phase II will extend the framework and develop two-demonstration applications--computer aided diagnosis (CAD) for mammography and multimodality image fusion. The ultimate goal is to obtain key partnerships and the private equity investment necessary for commercialization, which will proceed by launching revenue-generating versions of the CAD and image fusion applications.