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Abstrakty
Normal brain development is associated with expansion and folding of the cerebral cortex in a normal sequence of gyral–sulcal formation. We propose a global approach for measuring the cortical folding pattern of the developing brain. Our method measures geometric features directly on the cortical surface mesh, based on vertex labeling and skeletonization. The resulting extraction provides an accurate representation of global cortical organization. We applied this method to 17 young infants in order to characterize the evolution of cortical organization in the developing brain.
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161--166
Opis fizyczny
Bibliogr. 26 poz., rys., tab.
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- Montreal Children Hospital, McGill University, Montreal, Canada
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Bibliografia
- [1] RAKIC P. , Specification of cerebral cortical areas. Science, 241, 1988, pp. 170–176
- [2] ZILLES K., AMSTRONG E., SCHLEICHER A., and KRETSCHMANN H., The human pattern of gyrification in the human brain, Anat. Embryol., 1988, pp. 173–179.
- [3] MANGIN J.F., RIVIERE D., COULON O., POUPON C., CACHIA A., COINTEPAS Y., POLINE J.-B., BIHAN D. L., REGIS J., PAPADOPOULOS-ORFANOS D., Coordinate-based versus structural approaches to brain image analysis, Art. Intell. in Medicine, 30, 2004, pp. 177–197.
- [4] FISCHL B., SERENO M.I., TOOTELL R., DALE A.M., Cortical surface-based analysis, ii: Inflation, flattening and a surface-based coordinate system.NeuroImage 9, 1999, pp. 195–207.
- [5] VAN ESSEN D.C. and DRURY H.A., Structural and functional analyses of human cerebral cortex using a surface-based atlas, The Journal of Neuroscience, 17(18), 1997, pp. 7079– 7102.
- [6] MESULAM M.M., Principles of Behavioral and Cognitive Neurology, Second Edition. Oxford University Press, New York, 2000.
- [7] TALAIRACH J. and TOURNOUX P., Co-planar stereotaxic atlas of the human brain, 1988.
- [8] REGIS J., MANGIN J., OCHIAI T., FROUIN V., RIVIERE D., CACHIA A., TAMURA M., SAMSON Y., Sulcal roots generic model: a hypothesis to overcome the variability of the human cortex folding patterns, Neurol Med Chir, 45, 2005, pp. 1–17.
- [9] OHMANN G., VON CRAMON Y., and COLCHESTER A., Deep sulcal landmark an organizing framework for human cortical folding, Cereb. Cortex, 2007.
- [10] LEFEVRE J, LEROY F, KHAN S, DUBOIS J, HÜPPI P, BAILLET S, MANGIN J.F., Identification of growth seeds in the neonate brain through surfacic Helmholtz decomposition, IPMI, 2009.
- [11] TORO R., BURNOD Y., Geometric atlas: modeling the cortex as an organized surface, NeuroImage, 20(3), 2003, pp. 1468–1484.
- [12] CLOUCHOUX C., RIVIÈRE D., MANGIN J.F., OPERTO G., RÉGIS J., COULON O., Model-driven parameterization of the cortical surface for localization and inter-subject matching, NeuroImage, Vol. 50, n.2, 2010, pp. 552-566.
- [13] VAN ESSEN D., A tension-based theory of morphogenes is and compact wiring in the central nervous system, Nature, 385(23), 1997, pp. 313–318.
- [14] DUBOIS J. , BENDERS M., CACHIA A.,etal, Mapping the early cortical folding procès in the preterm new born brain, Cereb. Cor Advanc18, 2007, pp. 1444- 1454.
- [15] HILL J., DIERKER D., NEIL J., INDER T., KNUTSEN A, HARWELL J., COALSON T., VAN ESSEN D., A surface-based analysis of hemispheric asymmetries and folding of cerebral cortex in term-born human, J Neurosci.10;30(6), 2010, pp. 2268-76.
- [16] EVANS A.C. & the Brain Development Cooperative Group, The NIH MRI study of normal brain development, NeuroImage, 30 (1), 2006, pp. 184-202.
- [17] ZHANG Y., BRADY M., SMITH. S., Segmentation of brain MR images through a hidden Markov random field model and the expectation maximization algorithm, IEEE Trans. on Medical Imaging, 20(1), 2001, pp. 45-57.
- [18] MACDONALD D., et al., Automated 3-D Extraction of Inner and Outer Surfaces of Cerebral Cortex from MRI, NeuroImage. 12(3), 2000, pp. 340-356.
- [19] YOSHIZAWA S., BELYAEV A., SEIDEL H., Fast and robust detection of crest lines on meshes, ACM Symposium on Solid and Physical Modeling, 2005.
- [20] GOLDFEATHER J., INTERRANTE V., A novel cubic-order algorithm for approximating principal direction vectors, ACM Trans. Graph., 23(1), 2004, pp. 45–63.
- [21] GATZKE T., GRIMM C.M., Estimating curvature on triangular meshes, International Journal of Shape Modeling, 12(1), 2006, pp. 1–28.
- [22] KUDELSKI D., MARI J.L., VISEUR S., 3D Feature Line Detection based on Vertex Labeling and 2D Skeletonization, IEEE Int. Conference on Shape Modeling and Applications, 2010.
- [23] JAIN A. K., Fundamentals of digital image processing, Prentice-Hall, Inc, 1989.
- [24] RÖSSL C., KOBBELT L., SEIDEL H.P., Extraction of feature lines on triangulated surfaces using morphological operators, In Smart Graphics, AAAI Spring Symposium, 2010.
- [25] LYTTELTON O., BOUCHER M., ROBBINS S., EVANS A., An unbiased iterative group registration template for cortical surface analysis, NeuroImage, 10, 2006, pp. 1016.
- [26] MAZZIOTTA JC, TOGA AW, EVANS A, FOX P, LANCASTER J., A probabilistic atlas of the human brain: theory and rationale for its development, The International Consortium for Brain Mapping (ICBM) Neuroimage, 1995, pp. 2:89–101.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA4-0018-0020
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