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A Chinese multi-modal neuroimaging data release for increasing diversity of human brain mapping
The big-data use is becoming a standard practice in the neuroimaging field through data-sharing initiatives. It is important for the community to realize that such open science effort must protect personal, especially facial information when raw neuroimaging data are shared. An ideal tool for the fa...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9184635/ https://www.ncbi.nlm.nih.gov/pubmed/35680932 http://dx.doi.org/10.1038/s41597-022-01413-3 |
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author | Gao, Peng Dong, Hao-Ming Liu, Si-Man Fan, Xue-Ru Jiang, Chao Wang, Yin-Shan Margulies, Daniel Li, Hai-Fang Zuo, Xi-Nian |
author_facet | Gao, Peng Dong, Hao-Ming Liu, Si-Man Fan, Xue-Ru Jiang, Chao Wang, Yin-Shan Margulies, Daniel Li, Hai-Fang Zuo, Xi-Nian |
author_sort | Gao, Peng |
collection | PubMed |
description | The big-data use is becoming a standard practice in the neuroimaging field through data-sharing initiatives. It is important for the community to realize that such open science effort must protect personal, especially facial information when raw neuroimaging data are shared. An ideal tool for the face anonymization should not disturb subsequent brain tissue extraction and further morphological measurements. Using the high-resolution head images from magnetic resonance imaging (MRI) of 215 healthy Chinese, we discovered and validated a template effect on the face anonymization. Improved facial anonymization was achieved when the Chinese head templates but not the Western templates were applied to obscure the faces of Chinese brain images. This finding has critical implications for international brain imaging data-sharing. To facilitate the further investigation of potential culture-related impacts on and increase diversity of data-sharing for the human brain mapping, we released the 215 Chinese multi-modal MRI data into a database for imaging Chinese young brains, namely’I See your Brains (ISYB)’, to the public via the Science Data Bank (10.11922/sciencedb.00740). |
format | Online Article Text |
id | pubmed-9184635 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-91846352022-06-11 A Chinese multi-modal neuroimaging data release for increasing diversity of human brain mapping Gao, Peng Dong, Hao-Ming Liu, Si-Man Fan, Xue-Ru Jiang, Chao Wang, Yin-Shan Margulies, Daniel Li, Hai-Fang Zuo, Xi-Nian Sci Data Data Descriptor The big-data use is becoming a standard practice in the neuroimaging field through data-sharing initiatives. It is important for the community to realize that such open science effort must protect personal, especially facial information when raw neuroimaging data are shared. An ideal tool for the face anonymization should not disturb subsequent brain tissue extraction and further morphological measurements. Using the high-resolution head images from magnetic resonance imaging (MRI) of 215 healthy Chinese, we discovered and validated a template effect on the face anonymization. Improved facial anonymization was achieved when the Chinese head templates but not the Western templates were applied to obscure the faces of Chinese brain images. This finding has critical implications for international brain imaging data-sharing. To facilitate the further investigation of potential culture-related impacts on and increase diversity of data-sharing for the human brain mapping, we released the 215 Chinese multi-modal MRI data into a database for imaging Chinese young brains, namely’I See your Brains (ISYB)’, to the public via the Science Data Bank (10.11922/sciencedb.00740). Nature Publishing Group UK 2022-06-09 /pmc/articles/PMC9184635/ /pubmed/35680932 http://dx.doi.org/10.1038/s41597-022-01413-3 Text en © The Author(s) 2022 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Gao, Peng Dong, Hao-Ming Liu, Si-Man Fan, Xue-Ru Jiang, Chao Wang, Yin-Shan Margulies, Daniel Li, Hai-Fang Zuo, Xi-Nian A Chinese multi-modal neuroimaging data release for increasing diversity of human brain mapping |
title | A Chinese multi-modal neuroimaging data release for increasing diversity of human brain mapping |
title_full | A Chinese multi-modal neuroimaging data release for increasing diversity of human brain mapping |
title_fullStr | A Chinese multi-modal neuroimaging data release for increasing diversity of human brain mapping |
title_full_unstemmed | A Chinese multi-modal neuroimaging data release for increasing diversity of human brain mapping |
title_short | A Chinese multi-modal neuroimaging data release for increasing diversity of human brain mapping |
title_sort | chinese multi-modal neuroimaging data release for increasing diversity of human brain mapping |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9184635/ https://www.ncbi.nlm.nih.gov/pubmed/35680932 http://dx.doi.org/10.1038/s41597-022-01413-3 |
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