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The construction of a Chinese MRI brain atlas: a morphometric comparison study between Chinese and Caucasian cohorts.
Open accessAbstract
We developed a novel brain atlas template to facilitate computational brain studies of Chinese subjects and populations using high quality magnetic resonance imaging (MRI) and well-validated image analysis techniques. To explore the ethnicity-based structural brain differences, we used the MRI scans of 35 Chinese male subjects (24.03+/-2.06 years) and compared them to an age-matched cohort of 35 Caucasian males (24.03+/-2.06 years). Global volumetric measures were used to identify significant group differences in the brain length, width, height and AC-PC line distance. Using the LONI BrainParser, 56 brain structures were automatically labeled and analyzed for all subjects. We identified significant ethnicity differences in brain structure volumes, suggesting that a population-specific brain atlas may be more appropriate for studies involving Chinese populations. To address this, we constructed a 3D Chinese brain atlas based on high resolution 3.0T MRI scans of 56 right-handed male Chinese volunteers (24.46+/-1.81 years). All Chinese brains were spatially normalized by using linear and nonlinear transformation via the "AIR Make Atlas" pipeline workflow within the LONI pipeline environment. This high-resolution Chinese brain atlas was compared to the ICBM152 template, which was constructed using Caucasian brains.
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“both molecules are known to cross the blood brain barrier and interact with hippocampal cells (Ding et al., 2006; Tang et al., 2010).”
From Aerobic Exercise as a Tool to Improve Hippocampal Plasticity and Function in Humans: Practical Implications for Mental Health Treatment (2016) · cites this paper as Tang et al., 2010
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Cites
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“A brain template, or an atlas, provides a standard anatomical reference for individual or population based assessment of brain structure and function (Ashburner and Friston, 1999; Collins et al., 1994; Evans et al., 1993; Lancaster et al., 1999; Mazziotta et al., 2001; Toga and Thompson, 2001).”
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Research works printed but not linked: 1
- Kim, 2005, Development of a group_specific average brain atlas: a comparison study between Korean and Occidental groups, J. Biomed. Eng. Res., 26, 7
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“We first adjusted all variables for age and ethnicity (both of which may have been associated with differences in brain measures; Cox et al. 2016; Isamah et al. 2010; Tang et al. 2010).”
MethodFonseca, C. G., Backhaus, M., Bluemke, D. A., Britten, R. D., Chung, J. D., Cowan, B. R., Dinov, I. D., Finn, J. P., Hunter, P. J., Kadish, A. H., et al. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr360 · Cited by 292
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Znet: Deep Learning Approach for 2D MRI Brain Tumor Segmentation
Ottom, M. A., Rahman, H. A., & Dinov, I. D. (2022) · IEEE Journal of Translational Engineering in Health and Medicine · doi:10.1109/jtehm.2022.3176737 · Cited by 184
Bae, J. B., Lee, S., Jung, W., Park, S., Kim, W., Oh, H., Han, J. W., Kim, G. E., Kim, J. S., Kim, J. H., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-79243-9 · Cited by 171
Metadata
- Authors
- Tang, Y., Hojatkashani, C., Dinov, I. D., Sun, B., Fan, L., Lin, X., Qi, H., Hua, X., Liu, S., & Toga, A. W.
- Affiliations
- Shandong University (CN)
- University of California, Los Angeles (US)
- Corresponding author
- Liu, Shuwei
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2010-05
- Volume
- 51
- Issue
- 1
- Pages
- 33-41
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC2862912
- OpenAlex
- W2079062663
- Cited by
- 177
- References
- 52
- Citations by year
- 2026: 5 · 2025: 16 · 2024: 17 · 2023: 9 · 2022: 20 · 2021: 13 · 2020: 14 · 2019: 10 · 2018: 13 · 2017: 12 · 2016: 6 · 2015: 11 · 2014: 7 · 2013: 11 · 2012: 5
- FWCI
- 8.91
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Natural Science Foundation (30470905)
- National Institutes of Health (U54 RR021813, NIH/NCRR 5 P41 RR013642, NIH/NIMH 5 R01 MH71940)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- brain atlas construction, brain structure, brain volumetry, brain structure segmentation, 3T MRI, Chinese population
- MeSH terms
- Adult, Atlases as Topic, Automation, Brain, China, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Organ Size, Linear Models, Databases, Factual, Nonlinear Dynamics, Imaging, Three-Dimensional, White People, Asian People, Young Adult
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