Pan Tony C, Gurcan Metin N, Langella Stephen A, Oster Scott W, Hastings Shannon L, Sharma Ashish, Rutt Benjamin G, Ervin David W, Kurc Tahsin M, Siddiqui Khan M, Saltz Joel H, Siegel Eliot L
Department of Biomedical Informatics, Ohio State University, 3190 Graves Hall, 333 W 10th Ave, Columbus, OH 43210, USA.
Radiographics. 2007 May-Jun;27(3):889-97. doi: 10.1148/rg.273065153.
Grid computing-the use of a distributed network of electronic resources to cooperatively perform subsets of computationally intensive tasks-may help improve the speed and accuracy of radiologic image interpretation by enabling collaborative computer-based and human readings. GridCAD, a software application developed by using the National Cancer Institute Cancer Biomedical Informatics Grid architecture, implements the fundamental elements of grid computing and demonstrates the potential benefits of grid technology for medical imaging. It allows users to query local and remote image databases, view images, and simultaneously run multiple computer-assisted detection (CAD) algorithms on the images selected. The prototype CAD systems that are incorporated in the software application are designed for the detection of lung nodules on thoracic computed tomographic images. GridCAD displays the original full-resolution images with an overlay of nodule candidates detected by the CAD algorithms, by human observers, or by a combination of both types of readers. With an underlying framework that is computer platform independent and scalable to the task, the software application can support local and long-distance collaboration in both research and clinical practice through the efficient, secure, and reliable sharing of resources for image data mining, analysis, and archiving.
网格计算——利用分布式电子资源网络协同执行计算密集型任务的子集——通过实现基于计算机的协作式和人工读片，可能有助于提高放射影像解读的速度和准确性。GridCAD是一款利用美国国立癌症研究所癌症生物医学信息网格架构开发的软件应用程序，它实现了网格计算的基本要素，并展示了网格技术在医学成像方面的潜在益处。它允许用户查询本地和远程图像数据库、查看图像，并在所选图像上同时运行多个计算机辅助检测（CAD）算法。该软件应用程序中集成的原型CAD系统旨在检测胸部计算机断层扫描图像上的肺结节。GridCAD会显示原始的全分辨率图像，并叠加由CAD算法、人工观察者或两种类型的读片者共同检测到的结节候选区域。该软件应用程序具有一个独立于计算机平台且可根据任务进行扩展的底层框架，通过高效、安全和可靠地共享用于图像数据挖掘、分析和存档的资源，能够在研究和临床实践中支持本地和远程协作。
