Yang Ming, Yan Yaping, Wang He
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China.
Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai 200433, China.
Quant Imaging Med Surg. 2019 Feb;9(2):210-218. doi: 10.21037/qims.2018.12.03.
High-dimensional image data including diffusion weighted imaging, diffusion tensor imaging and dynamic imaging are important in exploring the connectivity, cellularity, pharmacokinetic and blood supply. IMAge/enGINE is software especially designed for high-dimensional medical image computing.
IMAge/enGINE is implemented based on open-source and cross-platform tools such as Qt, ITK and VTK. It processes the high-dimensional image data in a slice-by-slice computation mechanism. For computational efficiency, C++ is used for implementing IMAge/enGINE and multi-thread computing is handled in the scale of voxels. The architecture of IMAge/enGINE is modularized for easier extension.
IMAge/enGINE has following features: (I) IMAge/enGINE is free for research use; (II) it has an easy-to-use graphic user interface designed for clinical users without programming or engineering background; (III) its frame work is open-source and extensible. Developers can implement algorithms as modules and integrate them into IMAge/enGINE or generate their own application.
The source of IMAge/enGINE is hosted at https://github.com/VusionMed/IMAge-enGINE. Multiple diffusion and perfusion models are implemented and integrated into IMAge/enGINE and its binaries can be downloaded freely at http://www.vusion.com.cn/?page_id=14971.
包括扩散加权成像、扩散张量成像和动态成像在内的高维图像数据在探索连通性、细胞结构、药代动力学和血液供应方面具有重要意义。IMAge/enGINE是一款专门为高维医学图像计算设计的软件。
IMAge/enGINE基于Qt、ITK和VTK等开源和跨平台工具实现。它采用逐片计算机制处理高维图像数据。为提高计算效率,使用C++实现IMAge/enGINE,并在体素尺度上处理多线程计算。IMAge/enGINE的架构模块化,便于扩展。
IMAge/enGINE具有以下特点:(I)IMAge/enGINE供研究使用免费;(II)它有一个易于使用的图形用户界面,专为没有编程或工程背景的临床用户设计;(III)其框架是开源且可扩展的。开发者可以将算法作为模块实现并集成到IMAge/enGINE中,或者生成自己的应用程序。
IMAge/enGINE的源代码托管在https://github.com/VusionMed/IMAge-enGINE。多个扩散和灌注模型已实现并集成到IMAge/enGINE中,其二进制文件可在http://www.vusion.com.cn/?page_id=14971免费下载。