Infant Brain Atlases from Neonates to 1- and 2-Year-Olds
Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide additional guidance for the data processing such as spatial normalization, label propagation, and tissue segmentation. Although it is highly desire...
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Published in | PloS one Vol. 6; no. 4; p. e18746 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Public Library of Science
14.04.2011
Public Library of Science (PLoS) |
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Abstract | Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide additional guidance for the data processing such as spatial normalization, label propagation, and tissue segmentation. Although it is highly desired, there is currently no such infant atlas which caters for all these applications. The reason may be largely due to the dramatic early brain development, image processing difficulties, and the need of a large sample size.
To this end, after several years of subject recruitment and data acquisition, we have collected a unique longitudinal dataset, involving 95 normal infants (56 males and 39 females) with MRI scanned at 3 ages, i.e., neonate, 1-year-old, and 2-year-old. State-of-the-art MR image segmentation and registration techniques were employed, to construct which include the templates (grayscale average images), tissue probability maps (TPMs), and brain parcellation maps (i.e., meaningful anatomical regions of interest) for each age group. In addition, the longitudinal correspondences between age-specific atlases were also obtained. Experiments of typical infant applications validated that the proposed atlas outperformed other atlases and is hence very useful for infant-related studies.
We expect that the proposed infant 0-1-2 brain atlases would be significantly conducive to structural and functional studies of the infant brains. These atlases are publicly available in our website, http://bric.unc.edu/ideagroup/free-softwares/. |
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AbstractList | Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide additional guidance for the data processing such as spatial normalization, label propagation, and tissue segmentation. Although it is highly desired, there is currently no such infant atlas which caters for all these applications. The reason may be largely due to the dramatic early brain development, image processing difficulties, and the need of a large sample size.BACKGROUNDStudies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide additional guidance for the data processing such as spatial normalization, label propagation, and tissue segmentation. Although it is highly desired, there is currently no such infant atlas which caters for all these applications. The reason may be largely due to the dramatic early brain development, image processing difficulties, and the need of a large sample size.To this end, after several years of subject recruitment and data acquisition, we have collected a unique longitudinal dataset, involving 95 normal infants (56 males and 39 females) with MRI scanned at 3 ages, i.e., neonate, 1-year-old, and 2-year-old. State-of-the-art MR image segmentation and registration techniques were employed, to construct which include the templates (grayscale average images), tissue probability maps (TPMs), and brain parcellation maps (i.e., meaningful anatomical regions of interest) for each age group. In addition, the longitudinal correspondences between age-specific atlases were also obtained. Experiments of typical infant applications validated that the proposed atlas outperformed other atlases and is hence very useful for infant-related studies.METHODOLOGYTo this end, after several years of subject recruitment and data acquisition, we have collected a unique longitudinal dataset, involving 95 normal infants (56 males and 39 females) with MRI scanned at 3 ages, i.e., neonate, 1-year-old, and 2-year-old. State-of-the-art MR image segmentation and registration techniques were employed, to construct which include the templates (grayscale average images), tissue probability maps (TPMs), and brain parcellation maps (i.e., meaningful anatomical regions of interest) for each age group. In addition, the longitudinal correspondences between age-specific atlases were also obtained. Experiments of typical infant applications validated that the proposed atlas outperformed other atlases and is hence very useful for infant-related studies.We expect that the proposed infant 0-1-2 brain atlases would be significantly conducive to structural and functional studies of the infant brains. These atlases are publicly available in our website, http://bric.unc.edu/ideagroup/free-softwares/.CONCLUSIONSWe expect that the proposed infant 0-1-2 brain atlases would be significantly conducive to structural and functional studies of the infant brains. These atlases are publicly available in our website, http://bric.unc.edu/ideagroup/free-softwares/. Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide additional guidance for the data processing such as spatial normalization, label propagation, and tissue segmentation. Although it is highly desired, there is currently no such infant atlas which caters for all these applications. The reason may be largely due to the dramatic early brain development, image processing difficulties, and the need of a large sample size. To this end, after several years of subject recruitment and data acquisition, we have collected a unique longitudinal dataset, involving 95 normal infants (56 males and 39 females) with MRI scanned at 3 ages, i.e., neonate, 1-year-old, and 2-year-old. State-of-the-art MR image segmentation and registration techniques were employed, to construct which include the templates (grayscale average images), tissue probability maps (TPMs), and brain parcellation maps (i.e., meaningful anatomical regions of interest) for each age group. In addition, the longitudinal correspondences between age-specific atlases were also obtained. Experiments of typical infant applications validated that the proposed atlas outperformed other atlases and is hence very useful for infant-related studies. We expect that the proposed infant 0-1-2 brain atlases would be significantly conducive to structural and functional studies of the infant brains. These atlases are publicly available in our website, http://bric.unc.edu/ideagroup/free-softwares/. Background Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide additional guidance for the data processing such as spatial normalization, label propagation, and tissue segmentation. Although it is highly desired, there is currently no such infant atlas which caters for all these applications. The reason may be largely due to the dramatic early brain development, image processing difficulties, and the need of a large sample size. Methodology To this end, after several years of subject recruitment and data acquisition, we have collected a unique longitudinal dataset, involving 95 normal infants (56 males and 39 females) with MRI scanned at 3 ages, i.e., neonate, 1-year-old, and 2-year-old. State-of-the-art MR image segmentation and registration techniques were employed, to construct which include the templates (grayscale average images), tissue probability maps (TPMs), and brain parcellation maps (i.e., meaningful anatomical regions of interest) for each age group. In addition, the longitudinal correspondences between age-specific atlases were also obtained. Experiments of typical infant applications validated that the proposed atlas outperformed other atlases and is hence very useful for infant-related studies. Conclusions We expect that the proposed infant 0–1–2 brain atlases would be significantly conducive to structural and functional studies of the infant brains. These atlases are publicly available in our website, http://bric.unc.edu/ideagroup/free-softwares/. Background Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide additional guidance for the data processing such as spatial normalization, label propagation, and tissue segmentation. Although it is highly desired, there is currently no such infant atlas which caters for all these applications. The reason may be largely due to the dramatic early brain development, image processing difficulties, and the need of a large sample size. Methodology To this end, after several years of subject recruitment and data acquisition, we have collected a unique longitudinal dataset, involving 95 normal infants (56 males and 39 females) with MRI scanned at 3 ages, i.e., neonate, 1-year-old, and 2-year-old. State-of-the-art MR image segmentation and registration techniques were employed, to construct which include the templates (grayscale average images), tissue probability maps (TPMs), and brain parcellation maps (i.e., meaningful anatomical regions of interest) for each age group. In addition, the longitudinal correspondences between age-specific atlases were also obtained. Experiments of typical infant applications validated that the proposed atlas outperformed other atlases and is hence very useful for infant-related studies. Conclusions We expect that the proposed infant 0-1-2 brain atlases would be significantly conducive to structural and functional studies of the infant brains. These atlases are publicly available in our website, Background Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide additional guidance for the data processing such as spatial normalization, label propagation, and tissue segmentation. Although it is highly desired, there is currently no such infant atlas which caters for all these applications. The reason may be largely due to the dramatic early brain development, image processing difficulties, and the need of a large sample size. Methodology To this end, after several years of subject recruitment and data acquisition, we have collected a unique longitudinal dataset, involving 95 normal infants (56 males and 39 females) with MRI scanned at 3 ages, i.e., neonate, 1-year-old, and 2-year-old. State-of-the-art MR image segmentation and registration techniques were employed, to construct which include the templates (grayscale average images), tissue probability maps (TPMs), and brain parcellation maps (i.e., meaningful anatomical regions of interest) for each age group. In addition, the longitudinal correspondences between age-specific atlases were also obtained. Experiments of typical infant applications validated that the proposed atlas outperformed other atlases and is hence very useful for infant-related studies. Conclusions We expect that the proposed infant 0–1–2 brain atlases would be significantly conducive to structural and functional studies of the infant brains. These atlases are publicly available in our website, http://bric.unc.edu/ideagroup/free-softwares/. BackgroundStudies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide additional guidance for the data processing such as spatial normalization, label propagation, and tissue segmentation. Although it is highly desired, there is currently no such infant atlas which caters for all these applications. The reason may be largely due to the dramatic early brain development, image processing difficulties, and the need of a large sample size.MethodologyTo this end, after several years of subject recruitment and data acquisition, we have collected a unique longitudinal dataset, involving 95 normal infants (56 males and 39 females) with MRI scanned at 3 ages, i.e., neonate, 1-year-old, and 2-year-old. State-of-the-art MR image segmentation and registration techniques were employed, to construct which include the templates (grayscale average images), tissue probability maps (TPMs), and brain parcellation maps (i.e., meaningful anatomical regions of interest) for each age group. In addition, the longitudinal correspondences between age-specific atlases were also obtained. Experiments of typical infant applications validated that the proposed atlas outperformed other atlases and is hence very useful for infant-related studies.ConclusionsWe expect that the proposed infant 0-1-2 brain atlases would be significantly conducive to structural and functional studies of the infant brains. These atlases are publicly available in our website, http://bric.unc.edu/ideagroup/free-softwares/. Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide additional guidance for the data processing such as spatial normalization, label propagation, and tissue segmentation. Although it is highly desired, there is currently no such infant atlas which caters for all these applications. The reason may be largely due to the dramatic early brain development, image processing difficulties, and the need of a large sample size. To this end, after several years of subject recruitment and data acquisition, we have collected a unique longitudinal dataset, involving 95 normal infants (56 males and 39 females) with MRI scanned at 3 ages, i.e., neonate, 1-year-old, and 2-year-old. State-of-the-art MR image segmentation and registration techniques were employed, to construct which include the templates (grayscale average images), tissue probability maps (TPMs), and brain parcellation maps (i.e., meaningful anatomical regions of interest) for each age group. In addition, the longitudinal correspondences between age-specific atlases were also obtained. Experiments of typical infant applications validated that the proposed atlas outperformed other atlases and is hence very useful for infant-related studies. We expect that the proposed infant 0-1-2 brain atlases would be significantly conducive to structural and functional studies of the infant brains. These atlases are publicly available in our website, http://bric.unc.edu/ideagroup/free-softwares/. |
Audience | Academic |
Author | Wu, Guorong Jia, Hongjun Shi, Feng Yap, Pew-Thian Lin, Weili Gilmore, John H. Shen, Dinggang |
AuthorAffiliation | 3 MRI Lab, Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America 2 Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America 1 IDEA Lab, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America Tokyo Medical and Dental University, Japan |
AuthorAffiliation_xml | – name: 1 IDEA Lab, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America – name: Tokyo Medical and Dental University, Japan – name: 3 MRI Lab, Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America – name: 2 Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America |
Author_xml | – sequence: 1 givenname: Feng surname: Shi fullname: Shi, Feng – sequence: 2 givenname: Pew-Thian surname: Yap fullname: Yap, Pew-Thian – sequence: 3 givenname: Guorong surname: Wu fullname: Wu, Guorong – sequence: 4 givenname: Hongjun surname: Jia fullname: Jia, Hongjun – sequence: 5 givenname: John H. surname: Gilmore fullname: Gilmore, John H. – sequence: 6 givenname: Weili surname: Lin fullname: Lin, Weili – sequence: 7 givenname: Dinggang surname: Shen fullname: Shen, Dinggang |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/21533194$$D View this record in MEDLINE/PubMed |
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Cites_doi | 10.1016/j.neuroimage.2006.01.015 10.1109/42.963819 10.1016/j.neuroimage.2006.05.061 10.1136/jamia.1996.96236280 10.1109/2945.537306 10.1016/j.neuroimage.2010.02.025 10.1093/cercor/5.1.56 10.1006/nimg.1995.1012 10.1002/(SICI)1097-0193(1999)8:2/3<73::AID-HBM1>3.0.CO;2-7 10.1016/j.media.2005.05.007 10.1016/j.neuroimage.2008.07.060 10.1016/j.neuroimage.2007.07.030 10.1136/jamia.2001.0080401 10.1016/j.neuroimage.2004.07.068 10.1006/nimg.2001.0978 10.1016/S1053-8119(03)00185-X 10.2307/1932409 10.1002/hbm.10053 10.1523/JNEUROSCI.3339-06.2007 10.1002/(SICI)1097-0193(1999)7:4<254::AID-HBM4>3.0.CO;2-G 10.1016/j.neuroimage.2009.07.066 10.1097/00004728-199803000-00032 10.1016/j.neuroimage.2010.03.010 10.1109/TMI.2002.803111 10.1016/S0167-8655(98)00121-4 10.1016/j.neuroimage.2009.10.065 10.1016/j.neuroimage.2008.10.048 10.1109/42.668698 10.1016/j.neuroimage.2005.02.018 10.1002/hbm.20906 10.1098/rstb.2001.0915 10.1523/JNEUROSCI.3479-08.2008 10.1016/j.neuroimage.2009.02.043 10.1016/j.neuroimage.2007.05.004 10.1093/cercor/11.1.1 10.1016/j.neuroimage.2007.11.034 10.1016/j.neuroimage.2010.10.019 10.1016/j.media.2008.06.005 10.1007/s00791-002-0084-6 10.1016/j.neuroimage.2009.04.068 |
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References | H Jia (ref43) 2010; 51 J Ashburner (ref48) 2005; 26 S Baloch (ref38) 2009; 45 NI Weisenfeld (ref22) 2006 V Spitzer (ref10) 1996; 3 JC Mazziotta (ref7) 1995; 2 K Brodmann (ref5) 1909 S Tang (ref39) 2009; 47 PA Yushkevich (ref31) 2006; 31 JG Sled (ref32) 1998; 17 AW Toga (ref4) 2002 RA Heckemann (ref36) 2006; 33 RP Woods (ref14) 1999; 8 N Tzourio-Mazoyer (ref35) 2002; 15 J Mazziotta (ref9) 2001; 356 F Shi (ref25) 2010; 51 M Prastawa (ref19) 2005; 9 NI Weisenfeld (ref24) 2009; 47 H Xue (ref20) 2007; 38 RC Knickmeyer (ref17) 2008; 28 M Wilke (ref44) 2002; 17 S Joshi (ref42) 2004; 23 PM Thompson (ref15) 2001; 11 CJ Holmes (ref37) 1998; 22 PM Thompson (ref3) 2002; 5 M Kuklisova-Murgasova (ref26) 2010; 54 LR Dice (ref47) 1945; 26 J Ashburner (ref46) 1999; 7 E Armstrong (ref33) 1995; 5 J Talairach (ref6) 1988 Z Song (ref23) 2007 J Mazziotta (ref16) 2001; 8 AC Evans (ref8) 1993 K Kazemi (ref11) 2007; 37 DE Rex (ref45) 2003; 19 PA Habas (ref50) 2009 NI Weisenfeld (ref21) 2006 JD Van Horn (ref1) 2009 F Shi (ref28) 2010; 49 BTT Yeo (ref49) 2008; 12 JH Gilmore (ref18) 2007; 27 M Altaye (ref12) 2008; 43 D Shen (ref40) 2002; 21 T Rohlfing (ref13) 2010; 31 DW Shattuck (ref30) 2001; 20 R Kikinis (ref2) 1996; 2 G Wu (ref41) 2010; 49 G Wu (ref29) 2011 DL Pham (ref34) 1999; 20 IS Gousias (ref27) 2008; 40 |
References_xml | – volume: 31 start-page: 1116 year: 2006 ident: ref31 article-title: User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2006.01.015 – volume: 20 start-page: 1167 year: 2001 ident: ref30 article-title: Automated graph-based analysis and correction of cortical volume topology. publication-title: IEEE Transactions on Medical Imaging doi: 10.1109/42.963819 – volume: 33 start-page: 115 year: 2006 ident: ref36 article-title: Automatic anatomical brain MRI segmentation combining label propagation and decision fusion. publication-title: NeuroImage doi: 10.1016/j.neuroimage.2006.05.061 – volume: 3 start-page: 118 year: 1996 ident: ref10 article-title: The visible human male: a technical report. publication-title: Journal of the American Medical Informatics Association doi: 10.1136/jamia.1996.96236280 – year: 2011 ident: ref29 article-title: Feature-based Groupwise Registration by Hierarchical Anatomical Correspondence Detection. publication-title: Human Brain Mapping – year: 2002 ident: ref4 article-title: Brain mapping: The methods. – volume: 2 start-page: 232 year: 1996 ident: ref2 article-title: A digital brain atlas for surgical planning, model-drivensegmentation, and teaching. publication-title: IEEE Transactions on Visualization and Computer Graphics doi: 10.1109/2945.537306 – volume: 51 start-page: 684 year: 2010 ident: ref25 article-title: Construction of multi-region-multi-reference atlases for neonatal brain MRI segmentation. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2010.02.025 – volume: 5 start-page: 56 year: 1995 ident: ref33 article-title: The Ontogeny of Human Gyrification. publication-title: Cerebral Cortex doi: 10.1093/cercor/5.1.56 – start-page: 263 year: 2009 ident: ref1 article-title: Brain Atlases: Their Development and Role in Functional Inference. – volume: 2 start-page: 89 year: 1995 ident: ref7 article-title: A probabilistic atlas of the human brain: theory and rationale for its development. The International Consortium for Brain Mapping (ICBM). publication-title: Neuroimage doi: 10.1006/nimg.1995.1012 – volume: 8 start-page: 73 year: 1999 ident: ref14 article-title: Creation and use of a Talairach-compatible atlas for accurate, automated, nonlinear intersubject registration, and analysis of functional imaging data. publication-title: Human Brain Mapping doi: 10.1002/(SICI)1097-0193(1999)8:2/3<73::AID-HBM1>3.0.CO;2-7 – volume: 9 start-page: 457 year: 2005 ident: ref19 article-title: Automatic segmentation of MR images of the developing newborn brain. publication-title: Medical Image Analysis doi: 10.1016/j.media.2005.05.007 – volume: 43 start-page: 721 year: 2008 ident: ref12 article-title: Infant brain probability templates for MRI segmentation and normalization. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2008.07.060 – volume: 38 start-page: 461 year: 2007 ident: ref20 article-title: Automatic segmentation and reconstruction of the cortex from neonatal MRI. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2007.07.030 – volume: 8 start-page: 401 year: 2001 ident: ref16 article-title: A four-dimensional probabilistic atlas of the human brain. publication-title: Journal of the American Medical Informatics Association doi: 10.1136/jamia.2001.0080401 – start-page: 883 year: 2007 ident: ref23 article-title: Clinical neonatal brain MRI segmentation using adaptive nonparametric data models and intensity-based Markov priors. publication-title: MICCAI 2007 – volume: 23 start-page: 151 year: 2004 ident: ref42 article-title: Unbiased diffeomorphic atlas construction for computational anatomy. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2004.07.068 – start-page: 1813 year: 1993 ident: ref8 article-title: 3D statistical neuroanatomical models from 305 MRI volumes. publication-title: Proc IEEE-Nuclear Science Symposium and Medical Imaging Conference – start-page: 199 year: 2006 ident: ref21 article-title: Highly accurate segmentation of brain tissue and subcortical gray matter from newborn MRI. publication-title: MICCAI 2006 – year: 1988 ident: ref6 article-title: Co-planar stereotaxic atlas of the human brain – volume: 15 start-page: 273 year: 2002 ident: ref35 article-title: Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. publication-title: Neuroimage doi: 10.1006/nimg.2001.0978 – volume: 19 start-page: 1033 year: 2003 ident: ref45 article-title: The LONI Pipeline Processing Environment. publication-title: Neuroimage doi: 10.1016/S1053-8119(03)00185-X – volume: 26 start-page: 297 year: 1945 ident: ref47 article-title: Measures of the Amount of Ecologic Association Between Species. publication-title: Ecology doi: 10.2307/1932409 – volume: 17 start-page: 48 year: 2002 ident: ref44 article-title: Assessment of spatial normalization of whole-brain magnetic resonance images in children. publication-title: Human Brain Mapping doi: 10.1002/hbm.10053 – volume: 27 start-page: 1255 year: 2007 ident: ref18 article-title: Regional gray matter growth, sexual dimorphism, and cerebral asymmetry in the neonatal brain. publication-title: Journal of Neuroscience doi: 10.1523/JNEUROSCI.3339-06.2007 – volume: 7 start-page: 254 year: 1999 ident: ref46 article-title: Nonlinear spatial normalization using basis functions. publication-title: Human Brain Mapping doi: 10.1002/(SICI)1097-0193(1999)7:4<254::AID-HBM4>3.0.CO;2-G – volume: 49 start-page: 391 year: 2010 ident: ref28 article-title: Neonatal brain image segmentation in longitudinal MRI studies. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2009.07.066 – volume: 22 start-page: 324 year: 1998 ident: ref37 article-title: Enhancement of MR images using registration for signal averaging. publication-title: Journal of Computer Assisted Tomography doi: 10.1097/00004728-199803000-00032 – volume: 51 start-page: 1057 year: 2010 ident: ref43 article-title: ABSORB: Atlas Building by Self-organized Registration and Bundling. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2010.03.010 – volume: 21 start-page: 1421 year: 2002 ident: ref40 article-title: HAMMER: hierarchical attribute matching mechanism for elastic registration. publication-title: IEEE Transactions on Medical Imaging doi: 10.1109/TMI.2002.803111 – volume: 20 start-page: 57 year: 1999 ident: ref34 article-title: An adaptive fuzzy C-means algorithm for image segmentation in the presence of intensity inhomogeneities. publication-title: Pattern Recognition Letters doi: 10.1016/S0167-8655(98)00121-4 – volume: 49 start-page: 2225 year: 2010 ident: ref41 article-title: TPS-HAMMER: Improving HAMMER registration algorithm by soft correspondence matching and thin-plate splines based deformation interpolation. publication-title: NeuroImage doi: 10.1016/j.neuroimage.2009.10.065 – start-page: 766 year: 2006 ident: ref22 article-title: Segmentation of newborn brain MRI. publication-title: Macro to Nano – volume: 45 start-page: S73 year: 2009 ident: ref38 article-title: Morphological appearance manifolds in computational anatomy: Groupwise registration and morphological analysis. publication-title: NeuroImage doi: 10.1016/j.neuroimage.2008.10.048 – volume: 17 start-page: 87 year: 1998 ident: ref32 article-title: A nonparametric method for automatic correction of intensity nonuniformity in MRI data. publication-title: IEEE Trans Med Imaging doi: 10.1109/42.668698 – volume: 26 start-page: 839 year: 2005 ident: ref48 article-title: Unified segmentation. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2005.02.018 – volume: 31 start-page: 798 year: 2010 ident: ref13 article-title: The SRI24 multichannel atlas of normal adult human brain structure. publication-title: Human Brain Mapping doi: 10.1002/hbm.20906 – volume: 356 start-page: 1293 year: 2001 ident: ref9 article-title: A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). publication-title: Philos Trans R Soc Lond B Biol Sci doi: 10.1098/rstb.2001.0915 – volume: 28 start-page: 12176 year: 2008 ident: ref17 article-title: A structural MRI study of human brain development from birth to 2 years. publication-title: Journal of Neuroscience doi: 10.1523/JNEUROSCI.3479-08.2008 – volume: 47 start-page: 1277 year: 2009 ident: ref39 article-title: RABBIT: rapid alignment of brains by building intermediate templates. publication-title: NeuroImage doi: 10.1016/j.neuroimage.2009.02.043 – volume: 37 start-page: 463 year: 2007 ident: ref11 article-title: A neonatal atlas template for spatial normalization of whole-brain magnetic resonance images of newborns: preliminary results. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2007.05.004 – volume: 11 start-page: 1 year: 2001 ident: ref15 article-title: Cortical change in Alzheimer's disease detected with a disease-specific population-based brain atlas. publication-title: Cerebal Cortex doi: 10.1093/cercor/11.1.1 – volume: 40 start-page: 672 year: 2008 ident: ref27 article-title: Automatic segmentation of brain MRIs of 2-year-olds into 83 regions of interest. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2007.11.034 – volume: 54 start-page: 2750 year: 2010 ident: ref26 article-title: A dynamic 4D probabilistic atlas of the developing brain. publication-title: NeuroImage doi: 10.1016/j.neuroimage.2010.10.019 – volume: 12 start-page: 603 year: 2008 ident: ref49 article-title: Effects of registration regularization and atlas sharpness on segmentation accuracy. publication-title: Medical Image Analysis doi: 10.1016/j.media.2008.06.005 – volume: 5 start-page: 13 year: 2002 ident: ref3 article-title: A framework for computational anatomy. publication-title: Computing and Visualization in Science doi: 10.1007/s00791-002-0084-6 – year: 1909 ident: ref5 article-title: Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues. – volume: 47 start-page: 564 year: 2009 ident: ref24 article-title: Automatic segmentation of newborn brain MRI. publication-title: Neuroimage doi: 10.1016/j.neuroimage.2009.04.068 – start-page: 289 year: 2009 ident: ref50 article-title: A spatio-temporal atlas of the human fetal brain with application to tissue segmentation. publication-title: MICCAI 2009 |
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Snippet | Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide... Background Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can... BackgroundStudies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can... Background Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can... |
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SubjectTerms | Accuracy Adults Age Atlases as Topic Babies Bibliography Biology Brain Brain - anatomy & histology Brain mapping Child, Preschool Data acquisition Data processing Engineering Female Females Humans Image contrast Image processing Image segmentation Infant Infant, Newborn Infants Information processing Magnetic Resonance Imaging Male Males Medical imaging Medicine Morphology Neonates Neuroimaging Newborn babies Newborn infants Recruitment Registration Segmentation Structure-function relationships |
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Title | Infant Brain Atlases from Neonates to 1- and 2-Year-Olds |
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