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Using Large-Scale Statistical Chinese Brain Template (Chinese2020) in Popular Neuroimage Analysis Toolkits

Given that the morphology of Chinese brains statistically differs from that of Caucasian, there is an urgent need to develop a Chinese brain template for neuroimaging studies in Chinese populations. Based on a multi-center dataset, we developed a statistical Chinese brain template, named as Chinese2...

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Autores principales: Shi, Lin, Liang, Peipeng, Luo, Yishan, Liu, Kai, Mok, Vincent C. T., Chu, Winnie C. W., Wang, Defeng, Li, Kuncheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5562686/
https://www.ncbi.nlm.nih.gov/pubmed/28860982
http://dx.doi.org/10.3389/fnhum.2017.00414
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author Shi, Lin
Liang, Peipeng
Luo, Yishan
Liu, Kai
Mok, Vincent C. T.
Chu, Winnie C. W.
Wang, Defeng
Li, Kuncheng
author_facet Shi, Lin
Liang, Peipeng
Luo, Yishan
Liu, Kai
Mok, Vincent C. T.
Chu, Winnie C. W.
Wang, Defeng
Li, Kuncheng
author_sort Shi, Lin
collection PubMed
description Given that the morphology of Chinese brains statistically differs from that of Caucasian, there is an urgent need to develop a Chinese brain template for neuroimaging studies in Chinese populations. Based on a multi-center dataset, we developed a statistical Chinese brain template, named as Chinese2020 (Liang et al., 2015). This new Chinese brain atlas has been validated in brain normalization and segmentation for anatomical Magnetic Resonance Imaging (MRI) studies, and is publicly available at http://www.chinese-brain-atlases.org/. In our previous study, we have demonstrated this Chinese atlas showed higher accuracy in segmentation and relatively smaller shape deformations during registration. Because the spatial normalization of functional images is mainly based on the segmentation and normalization of anatomical image, the population-specific brain atlas should also be more appropriate for functional studies involving Chinese populations. The aim of this technology report is to validate the performance of Chinsese2020 template in functional neuroimaging studies, and demonstrated that for Chinese population studies, the use of the Chinese2010 template produces more valid results. The steps of how to use the Chinese2020 template in SPM software were given in details in this technology report, and based on an example of finger tapping fMRI study, this technology report demonstrated the Chinese2020 template could improve the performance of the neuroimaging analysis of Chinese populations.
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spelling pubmed-55626862017-08-31 Using Large-Scale Statistical Chinese Brain Template (Chinese2020) in Popular Neuroimage Analysis Toolkits Shi, Lin Liang, Peipeng Luo, Yishan Liu, Kai Mok, Vincent C. T. Chu, Winnie C. W. Wang, Defeng Li, Kuncheng Front Hum Neurosci Neuroscience Given that the morphology of Chinese brains statistically differs from that of Caucasian, there is an urgent need to develop a Chinese brain template for neuroimaging studies in Chinese populations. Based on a multi-center dataset, we developed a statistical Chinese brain template, named as Chinese2020 (Liang et al., 2015). This new Chinese brain atlas has been validated in brain normalization and segmentation for anatomical Magnetic Resonance Imaging (MRI) studies, and is publicly available at http://www.chinese-brain-atlases.org/. In our previous study, we have demonstrated this Chinese atlas showed higher accuracy in segmentation and relatively smaller shape deformations during registration. Because the spatial normalization of functional images is mainly based on the segmentation and normalization of anatomical image, the population-specific brain atlas should also be more appropriate for functional studies involving Chinese populations. The aim of this technology report is to validate the performance of Chinsese2020 template in functional neuroimaging studies, and demonstrated that for Chinese population studies, the use of the Chinese2010 template produces more valid results. The steps of how to use the Chinese2020 template in SPM software were given in details in this technology report, and based on an example of finger tapping fMRI study, this technology report demonstrated the Chinese2020 template could improve the performance of the neuroimaging analysis of Chinese populations. Frontiers Media S.A. 2017-08-17 /pmc/articles/PMC5562686/ /pubmed/28860982 http://dx.doi.org/10.3389/fnhum.2017.00414 Text en Copyright © 2017 Shi, Liang, Luo, Liu, Mok, Chu, Wang and Li. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Shi, Lin
Liang, Peipeng
Luo, Yishan
Liu, Kai
Mok, Vincent C. T.
Chu, Winnie C. W.
Wang, Defeng
Li, Kuncheng
Using Large-Scale Statistical Chinese Brain Template (Chinese2020) in Popular Neuroimage Analysis Toolkits
title Using Large-Scale Statistical Chinese Brain Template (Chinese2020) in Popular Neuroimage Analysis Toolkits
title_full Using Large-Scale Statistical Chinese Brain Template (Chinese2020) in Popular Neuroimage Analysis Toolkits
title_fullStr Using Large-Scale Statistical Chinese Brain Template (Chinese2020) in Popular Neuroimage Analysis Toolkits
title_full_unstemmed Using Large-Scale Statistical Chinese Brain Template (Chinese2020) in Popular Neuroimage Analysis Toolkits
title_short Using Large-Scale Statistical Chinese Brain Template (Chinese2020) in Popular Neuroimage Analysis Toolkits
title_sort using large-scale statistical chinese brain template (chinese2020) in popular neuroimage analysis toolkits
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5562686/
https://www.ncbi.nlm.nih.gov/pubmed/28860982
http://dx.doi.org/10.3389/fnhum.2017.00414
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