Unbiased construction of a temporally consistent morphological atlas of neonatal brain development
暂无分享,去创建一个
Daniel Rueckert | Mary A. Rutherford | Joseph V. Hajnal | Emma C. Robinson | Maria Murgasova | Anthony Price | Jana Hutter | Lucilio Cordero-Grande | Andreas Schuh | Antonios Makropoulos | Emer Hughes | Suresh Victor | Rui Pedro A. G. Teixeira | Nora Tusa | Johannes Steinweg | David A. Edwards | D. Rueckert | J. Hajnal | E. Robinson | A. Schuh | A. Price | N. Tusor | J. Hutter | L. Cordero-Grande | E. Hughes | J. Steinweg | M. Rutherford | M. Murgasova | A. Makropoulos | R. Teixeira | S. Victor | J. Hajnal | A. Edwards | Rui Pedro A. G. Teixeira | Lucilio Cordero-Grande | Rui Pedro A G Teixeira | M. Rutherford
[1] Thomas W. Sederberg,et al. Free-form deformation of solid geometric models , 1986, SIGGRAPH.
[2] Jean Meunier,et al. Automatic Computation of Average Brain Models , 1998, MICCAI.
[3] Ali R. Khan,et al. Symmetric Data Attachment Terms for Large Deformation Image Registration , 2007, IEEE Transactions on Medical Imaging.
[4] Paul Suetens,et al. Construction of a Brain Template from MR Images Using State-of-the-Art Registration and Segmentation Techniques , 2004, MICCAI.
[5] Alain Trouvé,et al. Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms , 2005, International Journal of Computer Vision.
[6] Ann-Beth Moller,et al. National, regional, and worldwide estimates of preterm birth rates in the year 2010 with time trends since 1990 for selected countries: a systematic analysis and implications , 2012, The Lancet.
[7] V. Arsigny,et al. Exponential Barycenters of the Canonical Cartan Connection and Invariant Means on Lie Groups , 2013 .
[8] Tom Vercauteren,et al. Diffeomorphic demons: Efficient non-parametric image registration , 2009, NeuroImage.
[9] Daniel Rueckert,et al. Magnetic resonance imaging of the newborn brain: Manual segmentation of labelled atlases in term-born and preterm infants , 2012, NeuroImage.
[10] Sébastien Ourselin,et al. Parametric non-rigid registration using a stationary velocity field , 2012, 2012 IEEE Workshop on Mathematical Methods in Biomedical Image Analysis.
[11] Karl J. Friston,et al. Identifying Global Anatomical Differences: Deformation-Based Morphometry , 1998, NeuroImage.
[12] Alejandro F. Frangi,et al. Temporal diffeomorphic free-form deformation: Application to motion and strain estimation from 3D echocardiography , 2012, Medical Image Anal..
[13] Seungyong Lee,et al. Injectivity Conditions of 2D and 3D Uniform Cubic B-Spline Functions , 2000, Graph. Model..
[14] Oscar Camara,et al. Toward the automatic quantification of in utero brain development in 3D structural MRI: A review , 2017, Human brain mapping.
[15] Michael I. Miller,et al. Deformable templates using large deformation kinematics , 1996, IEEE Trans. Image Process..
[16] L. R. Dice. Measures of the Amount of Ecologic Association Between Species , 1945 .
[17] Mary Rutherford,et al. Brain Maturation After Preterm Birth , 2013, Science Translational Medicine.
[18] Chris Adamson,et al. A new neonatal cortical and subcortical brain atlas: the Melbourne Children's Regional Infant Brain (M-CRIB) atlas , 2017, NeuroImage.
[19] Lana Vasung,et al. The role of neuroimaging in predicting neurodevelopmental outcomes of preterm neonates. , 2014, Clinics in perinatology.
[20] Peter Lorenzen,et al. Multi-modal image set registration and atlas formation , 2006, Medical Image Anal..
[21] Lilla Zöllei,et al. A unified information theoretic framework for pair- and group-wise registration of medical images , 2006 .
[22] M. Helfroush,et al. A Tool to Investigate Symmetry Properties of Newborns Brain: The Newborns' Symmetric Brain Atlas , 2013, ISRN neuroscience.
[23] Reinhard Grebe,et al. Symmetric brain atlas template for newborns brain asymmetry studies , 2013, 2013 21st Iranian Conference on Electrical Engineering (ICEE).
[24] Christos Davatzikos,et al. Comparative Evaluation of Registration Algorithms in Different Brain Databases With Varying Difficulty: Results and Insights , 2014, IEEE Transactions on Medical Imaging.
[25] Michael I. Miller,et al. Multi-contrast human neonatal brain atlas: Application to normal neonate development analysis , 2011, NeuroImage.
[26] Brian B. Avants,et al. Explicit B-spline regularization in diffeomorphic image registration , 2013, Front. Neuroinform..
[27] Ali R. Khan,et al. Symmetric Data Attachment Terms for Large , 2007 .
[28] Stephen M Smith,et al. Fast robust automated brain extraction , 2002, Human brain mapping.
[29] U. Grenander,et al. Computational anatomy: an emerging discipline , 1998 .
[30] Guido Gerig,et al. Unbiased diffeomorphic atlas construction for computational anatomy , 2004, NeuroImage.
[31] Daniel Rueckert,et al. Groupwise Combined Segmentation and Registration for Atlas Construction , 2007, MICCAI.
[32] J. Ashburner,et al. Nonlinear spatial normalization using basis functions , 1999, Human brain mapping.
[33] D. Louis Collins,et al. Tuning and Comparing Spatial Normalization Methods , 2003, MICCAI.
[34] Daniel Rueckert,et al. The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction , 2017, NeuroImage.
[35] Reinhard Grebe,et al. A Neonatal Bimodal MR-CT Head Template , 2017, PloS one.
[36] J. Hajnal,et al. Abnormal Cortical Development after Premature Birth Shown by Altered Allometric Scaling of Brain Growth , 2006, PLoS medicine.
[37] Daniel Rueckert,et al. Regional growth and atlasing of the developing human brain , 2016, NeuroImage.
[38] Marc Alexa,et al. Linear combination of transformations , 2002, ACM Trans. Graph..
[39] Mads Nielsen,et al. Kernel Bundle Diffeomorphic Image Registration Using Stationary Velocity Fields and Wendland Basis Functions , 2016, IEEE Transactions on Medical Imaging.
[40] Hamid Abrishami Moghaddam,et al. A neonatal atlas template for spatial normalization of whole-brain magnetic resonance images of newborns: Preliminary results , 2007, NeuroImage.
[41] Jana Hutter,et al. Three‐dimensional motion corrected sensitivity encoding reconstruction for multi‐shot multi‐slice MRI: Application to neonatal brain imaging , 2017, Magnetic resonance in medicine.
[42] Peter Lorenzen,et al. Unbiased Atlas Formation Via Large Deformations Metric Mapping , 2005, MICCAI.
[43] Sébastien Ourselin,et al. A parallel-friendly normalized mutual information gradient for free-form registration , 2009, Medical Imaging.
[44] Arno Klein,et al. Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration , 2009, NeuroImage.
[45] Colin Studholme,et al. A template free approach to volumetric spatial normalization of brain anatomy , 2004, Pattern Recognit. Lett..
[46] J. Gilmore,et al. Infant Brain Atlases from Neonates to 1- and 2-Year-Olds , 2011, PloS one.
[47] Nicholas Ayache,et al. Geometric Means in a Novel Vector Space Structure on Symmetric Positive-Definite Matrices , 2007, SIAM J. Matrix Anal. Appl..
[48] Daniel Rueckert,et al. Automatic Whole Brain MRI Segmentation of the Developing Neonatal Brain , 2014, IEEE Transactions on Medical Imaging.
[49] Colin Studholme. Simultaneous Population Based Image Alignment for Template Free Spatial Normalisation of Brain Anatomy , 2003, WBIR.
[50] Brian B. Avants,et al. The optimal template effect in hippocampus studies of diseased populations , 2010, NeuroImage.
[51] P. Thomas Fletcher,et al. Population Shape Regression from Random Design Data , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[52] John G. Sled,et al. Quantitative MRI for studying neonatal brain development , 2013, Neuroradiology.
[53] Dinggang Shen,et al. Feature‐based groupwise registration by hierarchical anatomical correspondence detection , 2012, Human brain mapping.
[54] J C Mazziotta,et al. Automated image registration: II. Intersubject validation of linear and nonlinear models. , 1998, Journal of computer assisted tomography.
[55] Daniel Rueckert,et al. Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data , 2015, MICCAI 2015.
[56] Michael I. Miller,et al. Multi-contrast large deformation diffeomorphic metric mapping for diffusion tensor imaging , 2009, NeuroImage.
[57] Sébastien Ourselin,et al. Fast free-form deformation using graphics processing units , 2010, Comput. Methods Programs Biomed..
[58] Nicholas Ayache,et al. A Log-Euclidean Framework for Statistics on Diffeomorphisms , 2006, MICCAI.
[59] Tomoki Arichi,et al. A dedicated neonatal brain imaging system , 2016, Magnetic resonance in medicine.
[60] Daniel Rueckert,et al. Nonrigid registration using free-form deformations: application to breast MR images , 1999, IEEE Transactions on Medical Imaging.
[61] Karl J. Friston,et al. Voxel-Based Morphometry—The Methods , 2000, NeuroImage.
[62] Paul M. Thompson,et al. A framework for computational anatomy , 2002 .
[63] John Ashburner,et al. A fast diffeomorphic image registration algorithm , 2007, NeuroImage.
[64] Brian B. Avants,et al. Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain , 2008, Medical Image Anal..
[65] Nicholas Ayache,et al. Symmetric Log-Domain Diffeomorphic Registration: A Demons-Based Approach , 2008, MICCAI.
[66] C. Boesch,et al. Structural and Neurobehavioral Delay in Postnatal Brain Development of Preterm Infants1 , 1996, Pediatric Research.
[67] Nicholas Ayache,et al. LCC-Demons: A robust and accurate symmetric diffeomorphic registration algorithm , 2013, NeuroImage.
[68] Daniel Rueckert,et al. A Multi-channel 4D Probabilistic Atlas of the Developing Brain: Application to Fetuses and Neonates , 2012 .
[69] Daniel Rueckert,et al. Consistent groupwise non-rigid registration for atlas construction , 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).
[70] Fabrice Heitz,et al. Symmetric Nonrigid Image Registration: Application to Average Brain Templates Construction , 2008, MICCAI.
[71] Terry S. Yoo,et al. Insight into Images: Principles and Practice for Segmentation, Registration, and Image Analysis , 2004 .
[72] Hong Wang,et al. Abnormal Cerebral Structure Is Present at Term in Premature Infants , 2005, Pediatrics.
[73] Simon K. Warfield,et al. A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth , 2017, Scientific Reports.
[74] Brian B. Avants,et al. N4ITK: Improved N3 Bias Correction , 2010, IEEE Transactions on Medical Imaging.
[75] Anders M. Dale,et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest , 2006, NeuroImage.
[76] Daniel Rueckert,et al. A dynamic 4D probabilistic atlas of the developing brain , 2011, NeuroImage.
[77] Daniel Rueckert,et al. Construction of a consistent high-definition spatio-temporal atlas of the developing brain using adaptive kernel regression , 2012, NeuroImage.
[78] Terrie E. Inder,et al. MRI of the Neonatal Brain , 2002 .
[79] Ernesto Zacur,et al. Algorithms for computing the group exponential of diffeomorphisms: Performance evaluation , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.
[80] Simon K. Warfield,et al. Construction of a Deformable Spatiotemporal MRI Atlas of the Fetal Brain: Evaluation of Similarity Metrics and Deformation Models , 2014, MICCAI.
[81] Dinggang Shen,et al. HAMMER: hierarchical attribute matching mechanism for elastic registration , 2002, IEEE Transactions on Medical Imaging.
[82] Monica Hernandez,et al. Contributions to 3D Diffeomorphic Atlas Estimation: Application to Brain Images , 2007, MICCAI.
[83] David Rey,et al. Symmetrization of the Non-rigid Registration Problem Using Inversion-Invariant Energies: Application to Multiple Sclerosis , 2000, MICCAI.
[84] Daniel Rueckert,et al. Diffeomorphic Registration Using B-Splines , 2006, MICCAI.