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Accelerated preprocessing of large numbers of brain images by parallel computing on supercomputers
“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 st...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10646110/ https://www.ncbi.nlm.nih.gov/pubmed/37963952 http://dx.doi.org/10.1038/s41598-023-46073-4 |
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author | Jimbo, Takehiro Matsuo, Hidetoshi Imoto, Yuya Sodemura, Takumi Nishimori, Makoto Fukui, Yoshinari Hayashi, Takuya Furuyashiki, Tomoyuki Yokoyama, Ryoichi |
author_facet | Jimbo, Takehiro Matsuo, Hidetoshi Imoto, Yuya Sodemura, Takumi Nishimori, Makoto Fukui, Yoshinari Hayashi, Takuya Furuyashiki, Tomoyuki Yokoyama, Ryoichi |
author_sort | Jimbo, Takehiro |
collection | PubMed |
description | “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. |
format | Online Article Text |
id | pubmed-10646110 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106461102023-11-14 Accelerated preprocessing of large numbers of brain images by parallel computing on supercomputers Jimbo, Takehiro Matsuo, Hidetoshi Imoto, Yuya Sodemura, Takumi Nishimori, Makoto Fukui, Yoshinari Hayashi, Takuya Furuyashiki, Tomoyuki Yokoyama, Ryoichi Sci Rep Article “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. Nature Publishing Group UK 2023-11-14 /pmc/articles/PMC10646110/ /pubmed/37963952 http://dx.doi.org/10.1038/s41598-023-46073-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Jimbo, Takehiro Matsuo, Hidetoshi Imoto, Yuya Sodemura, Takumi Nishimori, Makoto Fukui, Yoshinari Hayashi, Takuya Furuyashiki, Tomoyuki Yokoyama, Ryoichi Accelerated preprocessing of large numbers of brain images by parallel computing on supercomputers |
title | Accelerated preprocessing of large numbers of brain images by parallel computing on supercomputers |
title_full | Accelerated preprocessing of large numbers of brain images by parallel computing on supercomputers |
title_fullStr | Accelerated preprocessing of large numbers of brain images by parallel computing on supercomputers |
title_full_unstemmed | Accelerated preprocessing of large numbers of brain images by parallel computing on supercomputers |
title_short | Accelerated preprocessing of large numbers of brain images by parallel computing on supercomputers |
title_sort | accelerated preprocessing of large numbers of brain images by parallel computing on supercomputers |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10646110/ https://www.ncbi.nlm.nih.gov/pubmed/37963952 http://dx.doi.org/10.1038/s41598-023-46073-4 |
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