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BROCCOLI: Software for fast fMRI analysis on many-core CPUs and GPUs.

Anders Eklund1, Paul Dufort2, Mattias Villani3

  • 1Virginia Tech Carilion Research Institute, Virginia Tech Roanoke, VA, USA.

Frontiers in Neuroinformatics
|March 28, 2014
PubMed
Summary

BROCCOLI is a new, free software package that uses graphics processing units (GPUs) to significantly speed up the analysis of functional magnetic resonance imaging (fMRI) data, making complex neuroimaging more accessible.

Keywords:
CUDAGPUImage registrationNeuroimagingOpenCLPermutation testSpatial normalizationfMRI

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Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Medical Imaging Analysis

Background:

  • Functional magnetic resonance imaging (fMRI) data analysis is increasingly computationally intensive due to higher resolutions and larger datasets.
  • Advanced neuroimaging methods like non-linear spatial normalization and Bayesian approaches further escalate computational demands.
  • Existing fMRI software packages do not effectively utilize graphics processing units (GPUs) for analysis.

Purpose of the Study:

  • To introduce BROCCOLI, a novel, free software package designed for parallel fMRI data analysis.
  • To leverage graphics processing units (GPUs) for accelerating computationally demanding fMRI analyses.
  • To provide a versatile tool compatible with various hardware configurations.

Main Methods:

  • Developed BROCCOLI using OpenCL (Open Computing Language) for cross-platform GPU acceleration.
  • Tested BROCCOLI on diverse hardware, including CPUs and GPUs from Intel, Nvidia, and AMD.
  • Implemented parallel processing for fMRI data analysis tasks, including non-linear spatial normalization and non-parametric permutation tests.

Main Results:

  • BROCCOLI demonstrates significant speedups in fMRI analysis pipelines through parallel processing.
  • GPU acceleration with BROCCOLI drastically reduces analysis times for tasks like non-linear spatial normalization (4-6s) and permutation tests (~1 min).
  • The software supports advanced analyses, including Bayesian first-level fMRI analysis using Gibbs sampling.

Conclusions:

  • BROCCOLI offers a powerful and efficient solution for accelerating fMRI data analysis, particularly on GPU hardware.
  • The software enhances accessibility to complex neuroimaging analyses by reducing computational burden and time.
  • BROCCOLI is freely available, promoting wider adoption and advancement in the field of neuroimaging analysis.