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首页> 外文会议>Image Processing pt.3; Progress in Biomedical Optics and Imaging; vol.8,no.31; Proceedings of SPIE-The International Society for Optical Engineering; vol.6512 pt.3 >WHIPPET - a collaborative software environment for medical image processing and analysis
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WHIPPET - a collaborative software environment for medical image processing and analysis

机译：WHIPPET-用于医学图像处理和分析的协作软件环境

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摘要

While there are many publicly available software packages for medical image processing, making them available to end users in clinical and research labs remains non-trivial. An even more challenging task is to mix these packages to form pipelines that meet specific needs seamlessly, because each piece of software usually has its own input/output formats, parameter sets, and so on. To address these issues, we are building WHIPPET (Washington Heterogeneous Image Processing Pipeline EnvironmenT), a collaborative platform for integrating image analysis tools from different sources. The central idea is to develop a set of Python scripts which glue the different packages together and make it possible to connect them in processing pipelines. To achieve this, an analysis is carried out for each candidate package for WHIPPET, describing input/output formats, parameters, ROI description methods, scripting and extensibility and classifying its compatibility with other WHIPPET components as image file level, scripting level, function extension level, or source code level. We then identify components that can be connected in a pipeline directly via image format conversion. We set up a Twiki server for web-based collaboration so that component analysis and task request can be performed online, as well as project tracking, knowledge base management, and technical support. Currently WHIPPET includes the FSL, MIPAV, FreeSurfer, BrainSuite, Measure, DTIQuery, and 3D Slicer software packages, and is expanding. Users have identified several needed task modules and we report on their implementation.
机译：尽管有许多可公开获得的用于医学图像处理的软件包，但在临床和研究实验室中将其提供给最终用户仍然不容易。更具挑战性的任务是将这些软件包混合在一起以无缝地满足特定需求的流水线，因为每个软件通常都有自己的输入/输出格式，参数集等。为了解决这些问题，我们正在构建WHIPPET（华盛顿异构图像处理管道环境），这是一个集成来自不同来源的图像分析工具的协作平台。中心思想是开发一组Python脚本，将不同的软件包粘合在一起，并使它们可以在处理管道中连接。为此，针对WHIPPET的每个候选软件包进行了分析，描述了输入/输出格式，参数，ROI描述方法，脚本和可扩展性，并将其与其他WHIPPET组件的兼容性分类为图像文件级别，脚本级别，功能扩展级别。或源代码级别。然后，我们确定可以通过图像格式转换直接在管道中连接的组件。我们为基于Web的协作设置了一个Twiki服务器，以便可以在线执行组件分析和任务请求，以及项目跟踪，知识库管理和技术支持。当前，WHIPPET包括FSL，MIPAV，FreeSurfer，BrainSuite，Measure，DTIQuery和3D Slicer软件包，并且正在扩展。用户已经确定了几个所需的任务模块，我们将报告其实施情况。

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