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Accelerated preprocessing of large numbers of brain images by parallel computing on supercomputers.
Takehiro Jimbo1,2,3, Hidetoshi Matsuo4,5, Yuya Imoto1
1Japan Research Activity Support Inc., Kobe, Japan.
Supercomputers significantly accelerate brain image preprocessing, reducing analysis time for large datasets. This enables faster, more flexible big data analysis and future optimization of preprocessing techniques.
Area of Science:
- Neuroimaging
- Computational Neuroscience
- High-Performance Computing
Background:
- Brain image preprocessing is crucial for reliable analysis but is computationally intensive.
- Analyzing complex cortical structures requires significant processing time.
Purpose of the Study:
- To drastically reduce the time required for brain image data preprocessing.
- To evaluate the feasibility of using supercomputing for large-scale neuroimaging analysis.
Main Methods:
- Utilized the Fugaku supercomputer to process 1410 brain images simultaneously.
- Employed FreeSurfer as the benchmark software for cortical surface reconstruction.
Main Results:
- Successfully completed the preprocessing of all 1410 brain images in 17.33 hours.
- Demonstrated the efficiency of supercomputing for large-scale neuroimaging datasets.
Conclusions:
- Supercomputing offers a viable solution for rapid and flexible brain image preprocessing.
- Highlights the potential for supercomputers in expanding big data analysis and optimizing preprocessing parameters.
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