A study of the standard brain in Japanese children: Morphological comparison with the MNI template
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Daisuke Tanaka | Ayumi Seki | Tatsuya Koeda | T. Koeda | A. Seki | Hitoshi Uchiyama | Hitoshi T. Uchiyama | Daisuke Tanaka | JCS group | Jcs group
[1] Arthur W. Toga,et al. The construction of a Chinese MRI brain atlas: A morphometric comparison study between Chinese and Caucasian cohorts , 2010, NeuroImage.
[2] H. Engeland,et al. Variability in spatial normalization of pediatric and adult brain images , 2005, Clinical Neurophysiology.
[3] A. Seki,et al. Incidental Findings of Brain Magnetic Resonance Imaging Study in a Pediatric Cohort in Japan and Recommendation for a Model Management Protocol , 2010, Journal of epidemiology.
[4] Suzanne E. Welcome,et al. Mapping cortical change across the human life span , 2003, Nature Neuroscience.
[5] Kazunori Sato,et al. Neuroanatomical database of normal Japanese brains , 2003, Neural Networks.
[6] J. S. Lee,et al. Development of Korean Standard Brain Templates , 2005, Journal of Korean medical science.
[7] J. Talairach,et al. Co-Planar Stereotaxic Atlas of the Human Brain: 3-Dimensional Proportional System: An Approach to Cerebral Imaging , 1988 .
[8] Jyh-Horng Chen,et al. Development of NTU standard Chinese brain template: Morphologic and functional comparison with MNI template using magnetic resonance imaging , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[9] O. Muzik,et al. Statistical Parametric Mapping: Assessment of Application in Children , 2000, NeuroImage.
[10] Thomas F. Nugent,et al. Dynamic mapping of human cortical development during childhood through early adulthood. , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[11] A W Toga,et al. Maps of the Brain , 2001, The Anatomical record.
[12] Karl J. Friston,et al. Statistical parametric mapping , 2013 .
[13] Arthur W. Toga,et al. The myth of the normal, average human brain—The ICBM experience: (1) Subject screening and eligibility , 2009, NeuroImage.
[14] et al.,et al. The Effect of Template Choice on Morphometric Analysis of Pediatric Brain Data ☆ , 2022 .
[15] Hiroshi Fukuda,et al. Correlation between gray matter density‐adjusted brain perfusion and age using brain MR images of 202 healthy children , 2011, Human brain mapping.
[16] Alan C. Evans,et al. The NIH MRI study of normal brain development , 2006, NeuroImage.
[17] T. Schormann,et al. Hemispheric Shape of European and Japanese Brains: 3-D MRI Analysis of Intersubject Variability, Ethnical, and Gender Differences , 2001, NeuroImage.
[18] Terry M. Peters,et al. 3D statistical neuroanatomical models from 305 MRI volumes , 1993, 1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference.
[19] Scott Holland,et al. Template-O-Matic: A toolbox for creating customized pediatric templates , 2008, NeuroImage.
[20] D. Louis Collins,et al. Unbiased average age-appropriate atlases for pediatric studies , 2011, NeuroImage.
[21] Marko Wilke,et al. Assessment of spatial normalization of whole‐brain magnetic resonance images in children , 2002, Human brain mapping.
[22] J Mazziotta,et al. A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[23] Arthur W. Toga,et al. A Probabilistic Atlas of the Human Brain: Theory and Rationale for Its Development The International Consortium for Brain Mapping (ICBM) , 1995, NeuroImage.
[24] Hiroshi Fukuda,et al. Voxel-based morphometry of human brain with age and cerebrovascular risk factors , 2004, Neurobiology of Aging.