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The Java Image Science Toolkit (JIST) for Rapid Prototyping and Publishing of Neuroimaging Software

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An Erratum to this article was published on 09 March 2010

Abstract

Non-invasive neuroimaging techniques enable extraordinarily sensitive and specific in vivo study of the structure, functional response and connectivity of biological mechanisms. With these advanced methods comes a heavy reliance on computer-based processing, analysis and interpretation. While the neuroimaging community has produced many excellent academic and commercial tool packages, new tools are often required to interpret new modalities and paradigms. Developing custom tools and ensuring interoperability with existing tools is a significant hurdle. To address these limitations, we present a new framework for algorithm development that implicitly ensures tool interoperability, generates graphical user interfaces, provides advanced batch processing tools, and, most importantly, requires minimal additional programming or computational overhead. Java-based rapid prototyping with this system is an efficient and practical approach to evaluate new algorithms since the proposed system ensures that rapidly constructed prototypes are actually fully-functional processing modules with support for multiple GUI’s, a broad range of file formats, and distributed computation. Herein, we demonstrate MRI image processing with the proposed system for cortical surface extraction in large cross-sectional cohorts, provide a system for fully automated diffusion tensor image analysis, and illustrate how the system can be used as a simulation framework for the development of a new image analysis method. The system is released as open source under the Lesser GNU Public License (LGPL) through the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC).

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Acknowledgements

We greatly appreciate the unwavering support of Matt McAuliffe and Evan McCreedy of the NIH Center for Information Technology and the dedication of our undergraduate interns (Yufeng Guo, Robert Kim, Meenal Patel, Heba Mustufa, Hanlin Wan, and Jie Zhang). This work was supported by NIH/NINDS 5R01NS037747, 1R01NS056307, NIH/NIA N01-AG-4-0012 and NINDS 5R01NS054255.

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Correspondence to Bennett A. Landman.

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Information Sharing Statement

All source code for the JIST infrastructure is available in open source under the Lesser GNU Public License (LGPL) 2.1. Development is hosted by the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC, http://www.nitrc.org/projects/jist/). Anonymous read access to the source code is enabled, and build instructions can be found on the wiki (http://www.nitrc.org/plugins/mwiki/index.php/jist:AntBuild). Compiled versions of JIST and open source plug-ins are released on this site. Contributed, open source plug-ins are hosted on NITRC under LGPL 2.1 at http://www.nitrc.org/projects/jhumipavplugins/. Other open source and closed source JIST tools are available through the individual author’s websites (e.g., http://medic.rad.jhmi.edu/); the license mechanism for third party tools is not restricted by the JIST infrastructure license.

An erratum to this article can be found at http://dx.doi.org/10.1007/s12021-010-9065-y

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Lucas, B.C., Bogovic, J.A., Carass, A. et al. The Java Image Science Toolkit (JIST) for Rapid Prototyping and Publishing of Neuroimaging Software. Neuroinform 8, 5–17 (2010). https://doi.org/10.1007/s12021-009-9061-2

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