The application of grid computing to real-time functional MRI analysis

Authors:
E. Bagarinao;L. Sarmenta;Y. Tanaka;K. Matsuo;T. Nakai
Affiliations:
Photonics Research Institute, National Institute of Advanced Industrial Science and Technology (AIST) Kansai Center, Ikeda City, Osaka, Japan;Department of Information Systems and Computer Science, Ateneo de Manila University, Quezon City, Metro Manila, Philippines;Grid Research Technology Center, National Institute of Advanced Industrial Science and Technology, Tsukuba City, Ibaraki, Japan;Photonics Research Institute, National Institute of Advanced Industrial Science and Technology (AIST) Kansai Center, Ikeda City, Osaka, Japan;Photonics Research Institute, National Institute of Advanced Industrial Science and Technology (AIST) Kansai Center, Ikeda City, Osaka, Japan
Venue:
ISPA'04 Proceedings of the Second international conference on Parallel and Distributed Processing and Applications
Year:
2004

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Abstract

The analysis of brain imaging data such as functional MRI (fMRI) data often requires considerable computing resources, which in most cases are not readily available in many medical imaging facilities. This lack of computing power makes it difficult for researchers and medical practitioners alike to perform on-site analysis of the generated data. This paper proposes and demonstrates the use of Grid computing technology to provide medical imaging facilities with the capability of analyzing functional MRI data in real time with results available within seconds after data acquisition. Using PC clusters as analysis servers, and a software package that includes fMRI analysis tools, data transfer routines, and an easy-to-use graphical user interface, we are able to achieve fully real-time performance with a total processing time of 1.089 s per image volume (64 x 64 x 30 in size), much less than the per volume acquisition time set to 3.0 s. We also study the feasibility of using XML-based computational web services, and show how such web services can improve accessibility and interoperability while still making real-time analysis possible.