Unified Framework for Development, Deployment and Robust Testing of Neuroimaging Algorithms

作     者：Joshi, Alark Scheinost, Dustin Okuda, Hirohito Belhachemi, Dominique Murphy, Isabella Staib, Lawrence H. Papademetris, Xenophon 

作者机构：Yale Univ Dept Diagnost Radiol New Haven CT 06520 USA GE Healthcare Tokyo Japan 

出 版 物：《NEUROINFORMATICS》 (神经信息学)

年 卷 期：2011年第9卷第1期

页      面：69-84页

核心收录：

学科分类：1002[医学-临床医学] 1001[医学-基础医学(可授医学、理学学位)] 0812[工学-计算机科学与技术（可授工学、理学学位）] 10[医学] 

基　　金：NIH/NIBIB [R01 EB006494] 

主　　题：Neuroimaging software Open source medical imaging software Software development framework Comprehensive software testing 

摘      要：Developing both graphical and command-line user interfaces for neuroimaging algorithms requires considerable effort. Neuroimaging algorithms can meet their potential only if they can be easily and frequently used by their intended users. Deployment of a large suite of such algorithms on multiple platforms requires consistency of user interface controls, consistent results across various platforms and thorough testing. We present the design and implementation of a novel object-oriented framework that allows for rapid development of complex image analysis algorithms with many reusable components and the ability to easily add graphical user interface controls. Our framework also allows for simplified yet robust nightly testing of the algorithms to ensure stability and cross platform interoperability. All of the functionality is encapsulated into a software object requiring no separate source code for user interfaces, testing or deployment. This formulation makes our framework ideal for developing novel, stable and easy-to-use algorithms for medical image analysis and computer assisted interventions. The framework has been both deployed at Yale and released for public use in the open source multi-platform image analysis software-BioImage Suite (***).