Advantages of Multi-shell Diffusion for Studies of Brain Development in Youth
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Graham L. Baum | Adon F. G. Rosen | Adam R. Pines | D. Bassett | M. Cieslak | M. Elliott | P. Cook | D. Roalf | R. Shinohara | T. Satterthwaite | D. Oathes | A. Adebimpe | Diego G. Dávila | Robert J. Jirsaraie | Kristin Murtha | Kayla Piiwaa | Sage Rush
[1] Ninon Burgos,et al. New advances in the Clinica software platform for clinical neuroimaging studies , 2019 .
[2] C. Lebel,et al. A review of diffusion MRI of typical white matter development from early childhood to young adulthood , 2019, NMR in biomedicine.
[3] Hui Zhang,et al. Imaging brain microstructure with diffusion MRI: practicality and applications , 2019, NMR in biomedicine.
[4] Jean-Philippe Thiran,et al. Towards microstructure fingerprinting: Estimation of tissue properties from a dictionary of Monte Carlo diffusion MRI simulations , 2019, NeuroImage.
[5] Rachid Deriche,et al. Dmipy, a Diffusion Microstructure Imaging toolbox in Python to improve research reproducibility , 2018, MICCAI 2018.
[6] Catherine Lebel,et al. The development of brain white matter microstructure , 2018, NeuroImage.
[7] Leonardo L. Gollo,et al. Fragility and volatility of structural hubs in the human connectome , 2018, Nature Neuroscience.
[8] J. Gold,et al. On the nature and use of models in network neuroscience , 2018, Nature Reviews Neuroscience.
[9] Ragini Verma,et al. The impact of in-scanner head motion on structural connectivity derived from diffusion MRI , 2018, NeuroImage.
[10] M. Shenton,et al. Advanced diffusion imaging for assessing normal white matter development in neonates and characterizing aberrant development in congenital heart disease , 2018, NeuroImage: Clinical.
[11] Scott T. Grafton,et al. A probabilistic atlas of fiber crossings for variability reduction of anisotropy measures , 2018, Brain Structure and Function.
[12] Peter F. Neher,et al. The challenge of mapping the human connectome based on diffusion tractography , 2017, Nature Communications.
[13] C. Lebel,et al. Detailing neuroanatomical development in late childhood and early adolescence using NODDI , 2017, PloS one.
[14] Miho Ota,et al. Whole brain analyses of age-related microstructural changes quantified using different diffusional magnetic resonance imaging methods , 2017, Japanese Journal of Radiology.
[15] Hui Zhang,et al. Towards a comprehensive framework for movement and distortion correction of diffusion MR images: Within volume movement , 2017, NeuroImage.
[16] Scott Holland,et al. Neurite density index is sensitive to age related differences in the developing brain , 2017, NeuroImage.
[17] T. Paus,et al. Studying neuroanatomy using MRI , 2017, Nature Neuroscience.
[18] Graham L. Baum,et al. Modular Segregation of Structural Brain Networks Supports the Development of Executive Function in Youth , 2016, Current Biology.
[19] Rachid Deriche,et al. Diffusion MRI microstructure models with in vivo human brain Connectom data: results from a multi-group comparison , 2016, 1604.07287.
[20] T. Georgiou,et al. Microstructure Imaging of Crossing (MIX) White Matter Fibers from diffusion MRI , 2016, Scientific Reports.
[21] Stamatios N. Sotiropoulos,et al. Incorporating outlier detection and replacement into a non-parametric framework for movement and distortion correction of diffusion MR images , 2016, NeuroImage.
[22] Rachid Deriche,et al. MAPL: Tissue microstructure estimation using Laplacian-regularized MAP-MRI and its application to HCP data , 2016, NeuroImage.
[23] Yogesh Rathi,et al. Joint Multi-Fiber NODDI Parameter Estimation and Tractography Using the Unscented Information Filter , 2016, Front. Neurosci..
[24] C. Clark,et al. NODDI and Tensor-Based Microstructural Indices as Predictors of Functional Connectivity , 2016, PloS one.
[25] Thomas W. McAllister,et al. Age effects and sex differences in human brain white matter of young to middle-aged adults: A DTI, NODDI, and q-space study , 2016, NeuroImage.
[26] Ragini Verma,et al. The impact of quality assurance assessment on diffusion tensor imaging outcomes in a large-scale population-based cohort , 2016, NeuroImage.
[27] B. Schlaggar,et al. Considerations for MRI study design and implementation in pediatric and clinical populations , 2015, Developmental Cognitive Neuroscience.
[28] Paul Suetens,et al. Global tractography of multi-shell diffusion-weighted imaging data using a multi-tissue model , 2015, NeuroImage.
[29] Chris Rorden,et al. Reproducibility of the Structural Brain Connectome Derived from Diffusion Tensor Imaging , 2015, PloS one.
[30] S. Nagarajan,et al. White Matter Changes of Neurite Density and Fiber Orientation Dispersion during Human Brain Maturation , 2015, PloS one.
[31] Ben D. Fulcher,et al. Developmental Changes in Brain Network Hub Connectivity in Late Adolescence , 2015, The Journal of Neuroscience.
[32] Yong He,et al. Development of human brain structural networks through infancy and childhood. , 2015, Cerebral cortex.
[33] Sébastien Ourselin,et al. Longitudinal measurement of the developing grey matter in preterm subjects using multi-modal MRI , 2015, NeuroImage.
[34] Carl-Fredrik Westin,et al. Estimating Diffusion Propagator and Its Moments Using Directional Radial Basis Functions , 2015, IEEE Transactions on Medical Imaging.
[35] M. Chakravarty,et al. Functional Consequences of Neurite Orientation Dispersion and Density in Humans across the Adult Lifespan , 2015, The Journal of Neuroscience.
[36] Jean-Philippe Thiran,et al. Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data , 2015, NeuroImage.
[37] Arno Klein,et al. Large-scale evaluation of ANTs and FreeSurfer cortical thickness measurements , 2014, NeuroImage.
[38] I. Tsougos,et al. The role of diffusion and perfusion weighted imaging in the differential diagnosis of cerebral tumors: a review and future perspectives , 2014, Cancer Imaging.
[39] J. Wouters,et al. Diffusion Tensor Imaging and Resting-State Functional MRI-Scanning in 5- and 6-Year-Old Children: Training Protocol and Motion Assessment , 2014, PloS one.
[40] Maxime Descoteaux,et al. Dipy, a library for the analysis of diffusion MRI data , 2014, Front. Neuroinform..
[41] Krzysztof J. Gorgolewski,et al. Dynamic network participation of functional connectivity hubs assessed by resting-state fMRI , 2014, Front. Hum. Neurosci..
[42] Samuel D. Carpenter,et al. Structural and Functional Rich Club Organization of the Brain in Children and Adults , 2014, PloS one.
[43] Nancy Kanwisher,et al. Spurious group differences due to head motion in a diffusion MRI study , 2013, NeuroImage.
[44] Christos Davatzikos,et al. Heterogeneous impact of motion on fundamental patterns of developmental changes in functional connectivity during youth , 2013, NeuroImage.
[45] Timothy D. Verstynen,et al. Deterministic Diffusion Fiber Tracking Improved by Quantitative Anisotropy , 2013, PloS one.
[46] Derek K. Jones,et al. Investigating the prevalence of complex fiber configurations in white matter tissue with diffusion magnetic resonance imaging , 2013, Human brain mapping.
[47] Jan Sijbers,et al. Weighted linear least squares estimation of diffusion MRI parameters: Strengths, limitations, and pitfalls , 2013, NeuroImage.
[48] Victor Alves,et al. A hitchhiker's guide to diffusion tensor imaging , 2012, Front. Neurosci..
[49] Swathi P. Iyer,et al. Distinct neural signatures detected for ADHD subtypes after controlling for micro-movements in resting state functional connectivity MRI data , 2012, Front. Syst. Neurosci..
[50] Nadim Joni Shah,et al. Human cortical connectome reconstruction from diffusion weighted MRI: The effect of tractography algorithm , 2012, NeuroImage.
[51] Mark W. Woolrich,et al. FSL , 2012, NeuroImage.
[52] Daniel C. Alexander,et al. NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain , 2012, NeuroImage.
[53] Alan Connelly,et al. MRtrix: Diffusion tractography in crossing fiber regions , 2012, Int. J. Imaging Syst. Technol..
[54] Mark A. Elliott,et al. Impact of in-scanner head motion on multiple measures of functional connectivity: Relevance for studies of neurodevelopment in youth , 2012, NeuroImage.
[55] A. Mayer,et al. Head injury or head motion? Assessment and quantification of motion artifacts in diffusion tensor imaging studies , 2012, Human brain mapping.
[56] Kaustubh Supekar,et al. Dynamic Reconfiguration of Structural and Functional Connectivity Across Core Neurocognitive Brain Networks with Development , 2011, The Journal of Neuroscience.
[57] Hui Zhang,et al. Axon diameter mapping in the presence of orientation dispersion with diffusion MRI , 2011, NeuroImage.
[58] Brian B. Avants,et al. An Open Source Multivariate Framework for n-Tissue Segmentation with Evaluation on Public Data , 2011, Neuroinformatics.
[59] Dinggang Shen,et al. Brain anatomical networks in early human brain development , 2011, NeuroImage.
[60] Arno Klein,et al. A reproducible evaluation of ANTs similarity metric performance in brain image registration , 2011, NeuroImage.
[61] S. Wood. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models , 2011 .
[62] P. Basser,et al. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. 1996. , 1996, Journal of magnetic resonance.
[63] O. Sporns,et al. White matter maturation reshapes structural connectivity in the late developing human brain , 2010, Proceedings of the National Academy of Sciences.
[64] Tim B. Dyrby,et al. Orientationally invariant indices of axon diameter and density from diffusion MRI , 2010, NeuroImage.
[65] Mara Cercignani,et al. Twenty‐five pitfalls in the analysis of diffusion MRI data , 2010, NMR in biomedicine.
[66] Brian B. Avants,et al. N4ITK: Improved N3 Bias Correction , 2010, IEEE Transactions on Medical Imaging.
[67] V. Schmithorst,et al. White matter development during adolescence as shown by diffusion MRI , 2010, Brain and Cognition.
[68] Bruce Fischl,et al. Accurate and robust brain image alignment using boundary-based registration , 2009, NeuroImage.
[69] Arno Klein,et al. Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration , 2009, NeuroImage.
[70] Alexander Leemans,et al. Microstructural maturation of the human brain from childhood to adulthood , 2008, NeuroImage.
[71] R. Deriche,et al. Regularized, fast, and robust analytical Q‐ball imaging , 2007, Magnetic resonance in medicine.
[72] Y. Assaf,et al. Diffusion Tensor Imaging (DTI)-based White Matter Mapping in Brain Research: A Review , 2007, Journal of Molecular Neuroscience.
[73] A R Padhani,et al. Diffusion-weighted MRI: a new functional clinical technique for tumour imaging. , 2006, The British journal of radiology.
[74] Daniel C. Alexander,et al. Camino: Open-Source Diffusion-MRI Reconstruction and Processing , 2006 .
[75] Olaf Sporns,et al. The Human Connectome: A Structural Description of the Human Brain , 2005, PLoS Comput. Biol..
[76] Yaniv Assaf,et al. Composite hindered and restricted model of diffusion (CHARMED) MR imaging of the human brain , 2005, NeuroImage.
[77] Derek K. Jones,et al. “Squashing peanuts and smashing pumpkins”: How noise distorts diffusion‐weighted MR data , 2004, Magnetic resonance in medicine.
[78] S. Wood. Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models , 2004 .
[79] Philip A. Cook,et al. Modelling noise-induced fibre-orientation error in diffusion-tensor MRI , 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).
[80] M. Hedehus,et al. In vivo mapping of the fast and slow diffusion tensors in human brain , 2002, Magnetic resonance in medicine.
[81] Delores Saddler,et al. Research Review , 2012 .
[82] D. Le Bihan,et al. Water diffusion compartmentation and anisotropy at high b values in the human brain , 2000, Magnetic resonance in medicine.
[83] P. Basser,et al. In vivo fiber tractography using DT‐MRI data , 2000, Magnetic resonance in medicine.
[84] A. Szafer,et al. An analytical model of restricted diffusion in bovine optic nerve , 1997, Magnetic resonance in medicine.
[85] Karl J. Friston,et al. Movement‐Related effects in fMRI time‐series , 1996, Magnetic resonance in medicine.
[86] P. Basser,et al. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. , 1996, Journal of magnetic resonance. Series B.
[87] J. Bomanji,et al. Tumour imaging. , 1995, British journal of hospital medicine.
[88] P. Basser,et al. MR diffusion tensor spectroscopy and imaging. , 1994, Biophysical journal.
[89] J. Pekar,et al. MR color mapping of myelin fiber orientation. , 1991, Journal of computer assisted tomography.
[90] R. Turner,et al. Echo‐planar imaging of diffusion and perfusion , 1991, Magnetic resonance in medicine.
[91] G. Walter. Properties of Hermite Series Estimation of Probability Density , 1977 .
[92] J. E. Tanner,et al. Spin diffusion measurements : spin echoes in the presence of a time-dependent field gradient , 1965 .