Covington Kelsie, McCreedy Evan S, Chen Min, Carass Aaron, Aucoin Nicole, Landman Bennett A
Vanderbilt University, Department of Electrical Engineering, Nashville, TN 37215 USA.
Annu ORNL Biomed Sci Eng Cent Conf. 2010 May 25;2010:1-4. doi: 10.1109/BSEC.2010.5510850.
Clinical research with medical imaging typically involves large-scale data analysis with interdependent software toolsets tied together in a processing workflow. Numerous, complementary platforms are available, but these are not readily compatible in terms of workflows or data formats. Both image scientists and clinical investigators could benefit from using the framework which is a most natural fit to the specific problem at hand, but pragmatic choices often dictate that a compromise platform is used for collaboration. Manual merging of platforms through carefully tuned scripts has been effective, but exceptionally time consuming and is not feasible for large-scale integration efforts. Hence, the benefits of innovation are constrained by platform dependence. Removing this constraint via integration of algorithms from one framework into another is the focus of this work. We propose and demonstrate a light-weight interface system to expose parameters across platforms and provide seamless integration. In this initial effort, we focus on four platforms Medical Image Analysis and Visualization (MIPAV), Java Image Science Toolkit (JIST), command line tools, and 3D Slicer. We explore three case studies: (1) providing a system for MIPAV to expose internal algorithms and utilize these algorithms within JIST, (2) exposing JIST modules through self-documenting command line interface for inclusion in scripting environments, and (3) detecting and using JIST modules in 3D Slicer. We review the challenges and opportunities for light-weight software integration both within development language (e.g., Java in MIPAV and JIST) and across languages (e.g., C/C++ in 3D Slicer and shell in command line tools).
医学成像的临床研究通常涉及大规模数据分析，在处理工作流程中相互关联的软件工具集紧密相连。有许多互补的平台可供使用，但这些平台在工作流程或数据格式方面并不容易兼容。图像科学家和临床研究人员都可以从使用最适合手头特定问题的框架中受益，但实际选择往往决定使用折中的平台进行协作。通过精心调整的脚本手动合并平台是有效的，但异常耗时，对于大规模集成工作来说并不可行。因此，创新的好处受到平台依赖性的限制。通过将一个框架中的算法集成到另一个框架中来消除这种限制是这项工作的重点。我们提出并演示了一个轻量级接口系统，以跨平台公开参数并提供无缝集成。在这项初步工作中，我们专注于四个平台：医学图像分析与可视化（MIPAV）、Java图像科学工具包（JIST）、命令行工具和3D Slicer。我们探索了三个案例研究：（1）为MIPAV提供一个系统，以公开其内部算法并在JIST中使用这些算法；（2）通过自记录命令行界面公开JIST模块，以便包含在脚本环境中；（3）在3D Slicer中检测并使用JIST模块。我们回顾了在开发语言（例如，MIPAV和JIST中的Java）内部以及跨语言（例如，3D Slicer中的C/C++和命令行工具中的shell）进行轻量级软件集成的挑战和机遇。
