Summary
Objectives:
The analysis of brain imaging data such as functional MRI 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 presents a system that is capable of analyzing functional MRI data in real
time with results available within seconds after data acquisition.
Methods:
The system employs remote computational servers to provide the necessary computing
power. System integration is accomplished by an accompanying software package, which
includes fMRI analysis tools, data transfer routines, and an easy-to-use graphical
user interface. The remote analysis is transparent to the user as if all computations
are performed locally.
Results:
The use of PC clusters in the analysis of fMRI data significantly improved the performance
of the system. Simulation runs fully achieved 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.
Conclusions:
The results show the feasibility of using remote computational resources to enable
on-demand real-time fMRI capabilities to imaging sites. It also offers the possibility
of doing more intensive analysis even if the imaging site doesn’t have the necessary
computing resources.
Keywords
On-demand real-time fMRI analysis - computational grids - incremental GLM analysis
