Langer Steve, Charboneau Nick, French Todd
Mayo Clinic, Rochester, MN, USA.
J Digit Imaging. 2010 Dec;23(6):681-8. doi: 10.1007/s10278-009-9230-8. Epub 2009 Aug 25.
Medical Imaging has been fortunate to see an avalanche of free and open source software become available in the last several years. Applications have been written to enable image viewing/storage/analysis/processing, DICOM and HL7 message parsing, results aggregation, anonymization, and more. While robust, many of these packages are difficult to install and configure. Our group desired an approach that would mitigate the efforts required to use these packages across different projects. We found such a solution in the context of using virtual machines.
在过去几年里,医学成像领域有幸见证了大量免费和开源软件的涌现。人们编写了各种应用程序,用于图像查看/存储/分析/处理、DICOM和HL7消息解析、结果汇总、匿名化等等。虽然这些软件包功能强大,但其中许多都难以安装和配置。我们团队希望找到一种方法,来减轻在不同项目中使用这些软件包所需的工作量。我们在使用虚拟机的背景下找到了这样一种解决方案。