面向浏览器的医学影像可视化系统

目的 当前各大商业公司和开源社区所提供的医学影像可视化系统依赖于各类平台以及与平台相关的插件,难以实现跨平台访问.为此提出并实现了基于HTML5的面向现代浏览器的医学影像可视化系统.方法 基于B/S(browers/server)模式进行系统整体架构与设计,设计自定义的传输协议提供各种定制的图像可视化服务.对于2维影像,采用HTML的canvas技术和WebGL技术进行浏览器端硬件加速.对于3维医学影像,采用前后端异步操作的策略以提供渐进式可视化.算法构造原始数据的多分辨率采样,并在用户交互过程中实现自适应可视化.结果 在不同的浏览器、多组临床医学影像肝脏数据上测试了系统,表明系统支持跨浏览器的可视化.测试2维和3维可视化的结果表明,系统支持2维影像的实时可视化(25帧/s),支持3维影像的交互可视化.对于512×512×154的医学体数据,低精度绘制模式的可视化效率可以达到60帧/s,高精度绘制模式的可视化效率可达到 1帧/s 的绘制效率.结论 本文面向浏览器的医学影像可视化系统利用当下新兴的WEB技术实现了跨浏览器、跨平台地对用户提供服务,为远程及移动医疗影像可视化系统提供了机会.

HTML5-based medical image visualization system

Objective Most existing medical systems provided by major commercial companies and open source communities depend on different operating systems and platform-related plug-ins.Thus, cross-platform access is difficult to provide. This study presents a browser-oriented medical image visualization system based on the latest web technology and HTML5. Method Our approach is designed on the basis of B/S mode. The proposed method employs a self-defined protocol to offer customized visualization services. In particular, we propose the Canvas technique for HTML4 and WebGL to accelerate browser visualization. We propose an asynchronous approach to provide progressive visualization. This approach constructs multi-resolution sampling data for the underlying dataset and employs an adaptive visualization scheme during user interactions. Result We tested our system using multiple clinical and medical datasets in different browsers. Results show that our system supports multiple browsers. Experiments on 2D and 3D visualization features show that our system can display 2D images in real-time (25 frame/s), as well as visualize 3D images interactively. For a dataset with a resolution of 512×512×154, low-resolution sampling performance achieves 60 frame/s), whereas that of high-resolution sampling is 1 frame/s). Conclusion The proposed system fully supports cross-platform operation and is compatible with all browsers that support HTML5. These features significantly enhance user experience and openup prospects for remote and mobile medical image visualization systems, as well as give rise to a new opportunity for web medical image visualization systems.