The Java Image Science Toolkit (JIST) for Rapid Prototyping and Publishing of Neuroimaging Software
- 944 Downloads
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).
KeywordsParallel processing Pipeline Rapid prototyping Image processing MRI
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.
- Bazin, P., & Pham, D. (2006). TOADS: topology-preserving, anatomy-driven segmentation. Biomedical Imaging: Macro to Nano, 2006. 3rd IEEE International Symposium on.Google Scholar
- Bull, J. M., Smith L. A., et al. (2001). Benchmarking Java against C and Fortran for scientific applications. EPCC.Google Scholar
- Burnett, M., & McIntyre, D. (1995). Visual programming. Computer, 14–16.Google Scholar
- Cook, P. A., Bai, Y., et al. (2006). Camino: Open-source diffusion-MRI reconstruction and processing. Seattle: 14th Scientific Meeting of the International Society for Magnetic Resonance in Medicine.Google Scholar
- Foundation, F. S. (2007). Lesser general public license. from http://www.gnu.org/licenses/lgpl-2.1.txt.
- Landman, B., Bogovic, J., et al. (2008). Compressed sensing of multiple intra-voxel orientations with traditional DTI. Proc Workshop on Computational Diffussion MRI, MICCAI 2008.Google Scholar
- Lucas, B., Abram, G., et al. (1992). An architecture for a scientific visualization system.Google Scholar
- McAuliffe, M., Lalonde, F., et al. (2001). Medical image processing, analysis and visualization in clinical research. Computer-Based Medical Systems, 2001. 14th IEEE Symposium on.Google Scholar
- Mori, S., Crain, B., et al. (1999). Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Annals of Neurology, 45(2).Google Scholar
- Mulshine, J. L., & Baer, T. M. (2008). Quantitative Imaging Tools for Lung Cancer Drug Assessment. Wiley-OSA.Google Scholar
- Parker, S., & Johnson, C. (1995). SCIRun: A scientific programming environment for computational steering. NY: ACM New York.Google Scholar
- Pieper, S., Lorensen, B., et al. (2006). The NA-MIC Kit: ITK, VTK, pipelines, grids and 3D slicer as an open platform for the medical image computing community. Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on.Google Scholar
- Rajic, H., Brobst, R., et al. (2004). Distributed resource management application API specification 1.0. from http://www.ggf.org/documents/GWD-R/GFD-R.022.pdf.
- Schroeder, W., Martin, K., et al. (1996). The design and implementation of an object-oriented toolkit for 3D graphics and visualization. Visualization, 1996. 7th IEEE Conference on.Google Scholar
- Tosun, D., Rettmann, M., et al. (2004a). Cortical reconstruction using implicit surface evolution: a landmark validation study. Lecture Notes in Computer Science, 384–392.Google Scholar
- Yoo, T. (2004). Insight into images, A.K. Peters.Google Scholar
- Yoo, T., Ackerman, M., et al. (2002). Engineering and algorithm design for an image processing API: a technical report on ITK-the insight toolkit. Studies Health Technology and Informatics, 85, 586–592.Google Scholar