ArticleScientific reports2023
Accelerated preprocessing of large numbers of brain images by parallel computing on supercomputers.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Massively parallelized brain tractography using compute clusters, supercomputers, and graphics processing units.Imaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
- Erratum issued
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
"Preprocessing" is the first step required in brain image analysis that improves the overall quality and reliability of the results. However, it is computationally demanding and time-consuming, particularly to handle and parcellate complicatedly folded cortical ribbons of the human brain. In this study, we aimed to shorten the analysis time for data preprocessing of 1410 brain images simultaneously on one of the world's highest-performing supercomputers, "Fugaku." The FreeSurfer was used as a benchmark preprocessing software for cortical surface reconstruction. All the brain images were processed simultaneously and successfully analyzed in a calculation time of 17.33 h. This result indicates that using a supercomputer for brain image preprocessing allows big data analysis to be completed shortly and flexibly, thus suggesting the possibility of supercomputers being used for expanding large data analysis and parameter optimization of preprocessing in the future.
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