Cortical thickness computation by solving tetrahedron-based harmonic field
暂无分享,去创建一个
Gang Wang | Tao Yao | Liang Xiao | Qingtang Su | Xiaofeng Zhang | Deping Kong | Yonghui Fan | Jinguang Hao | Caiming Zhang | G. Wang | Caiming Zhang | Xiaofeng Zhang | Qingtang Su | T. Yao | Liang Xiao | Deping Kong | Jinguang Hao | Yonghui Fan
[1] Hang Si,et al. TetGen, a Delaunay-Based Quality Tetrahedral Mesh Generator , 2015, ACM Trans. Math. Softw..
[2] Gang Wang,et al. A Tetrahedron-Based Heat Flux Signature for Cortical Thickness Morphometry Analysis , 2018, MICCAI.
[3] Jyrki Lötjönen,et al. Measurement of hippocampal atrophy using 4D graph-cut segmentation: Application to ADNI , 2010, NeuroImage.
[4] Margot J. Taylor,et al. Measures of Cortical Grey Matter Structure and Development in Children with Autism Spectrum Disorder , 2011, Journal of Autism and Developmental Disorders.
[5] Kevin Weiler. Topological Structures for Geometric Modeling , 1986 .
[6] Liang Xu,et al. Combining Thickness Information with Surface Tensor-based Morphometry for the 3D Statistical Analysis of the Corpus Callosum , 2013 .
[7] Kiralee M. Hayashi,et al. Dynamics of Gray Matter Loss in Alzheimer's Disease , 2003, The Journal of Neuroscience.
[8] Daniel Bandy,et al. Hippocampal volumes in cognitively normal persons at genetic risk for Alzheimer's disease , 1998, Annals of neurology.
[9] A. Fagan,et al. Cerebrospinal fluid tau/beta-amyloid(42) ratio as a prediction of cognitive decline in nondemented older adults. , 2007, Archives of neurology.
[10] Gunhild Waldemar,et al. The potential of microRNAs as biofluid markers of neurodegenerative diseases – a systematic review , 2014, Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals.
[11] C. Jack,et al. Atrophy rates accelerate in amnestic mild cognitive impairment , 2008, Neurology.
[12] Michel Behr,et al. Forces transmission to the skull in case of mandibular impact. , 2015, Forensic science international.
[13] Richard J. Caselli,et al. Correlations Between Apolipoprotein E ε4 Gene Dose and Whole Brain Atrophy Rates , 2007 .
[14] Andrey N. Chernikov,et al. Mesh deformation-based multi-tissue mesh generation for brain images , 2012, Engineering with Computers.
[15] Denise C. Park,et al. Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease , 2011, Alzheimer's & Dementia.
[16] Anders M. Dale,et al. Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.
[17] A. Dale,et al. Whole Brain Segmentation Automated Labeling of Neuroanatomical Structures in the Human Brain , 2002, Neuron.
[18] G. Alexander,et al. Declining brain activity in cognitively normal apolipoprotein E ɛ4 heterozygotes: A foundation for using positron emission tomography to efficiently test treatments to prevent Alzheimer's disease , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[19] M N Rossor,et al. Correlation between rates of brain atrophy and cognitive decline in AD , 1999, Neurology.
[20] Jean-Francois Mangin,et al. A Library of Cortical Morphology Analysis Tools to Study Development, Aging and Genetics of Cerebral Cortex , 2011, Neuroinformatics.
[21] G. Alexander,et al. Longitudinal PET Evaluation of Cerebral Metabolic Decline in Dementia: A Potential Outcome Measure in Alzheimer's Disease Treatment Studies. , 2002, The American journal of psychiatry.
[22] Sébastien Ourselin,et al. A comparison of voxel and surface based cortical thickness estimation methods , 2011, NeuroImage.
[23] I. Aharon,et al. Three‐dimensional mapping of cortical thickness using Laplace's Equation , 2000, Human brain mapping.
[24] C. Jack,et al. Brain beta-amyloid measures and magnetic resonance imaging atrophy both predict time-to-progression from mild cognitive impairment to Alzheimer’s disease , 2010, Brain : a journal of neurology.
[25] Bernard R. Rosner,et al. Fundamentals of Biostatistics. , 1992 .
[26] J. Weuve,et al. Alzheimer disease in the United States (2010–2050) estimated using the 2010 census , 2013, Neurology.
[27] Clifford R. Jack,et al. Predicting Clinical Scores from Magnetic Resonance Scans in Alzheimer's Disease , 2010, NeuroImage.
[28] A. Dale,et al. Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System , 1999, NeuroImage.
[29] C. Studholme,et al. Brain atrophy associated with baseline and longitudinal measures of cognition , 2011, Neurobiology of Aging.
[30] R. Petersen,et al. Cerebrospinal fluid biomarker signature in Alzheimer's disease neuroimaging initiative subjects , 2009, Annals of neurology.
[31] Nick C Fox,et al. The clinical use of structural MRI in Alzheimer disease , 2010, Nature Reviews Neurology.
[32] Lothar Lilge,et al. FullMonte: a framework for high-performance Monte Carlo simulation of light through turbid media with complex geometry , 2013, Photonics West - Biomedical Optics.
[33] Paul M. Thompson,et al. Mapping hippocampal and ventricular change in Alzheimer disease , 2004, NeuroImage.
[34] Martti Mäntylä,et al. Introduction to Solid Modeling , 1988 .
[35] Wiro J Niessen,et al. A 10-year follow-up of hippocampal volume on magnetic resonance imaging in early dementia and cognitive decline. , 2010, Brain : a journal of neurology.
[36] Paul M. Thompson,et al. Volumetric harmonic brain mapping , 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).
[37] M. Krízek,et al. On the maximum angle condition for linear tetrahedral elements , 1992 .
[38] Simon K. Warfield,et al. Anisotropic partial volume CSF modeling for EEG source localization , 2012, NeuroImage.
[39] C. Jack,et al. MRI as a biomarker of disease progression in a therapeutic trial of milameline for AD , 2003, Neurology.
[40] C. Jack,et al. Preclinical Alzheimer's disease: Definition, natural history, and diagnostic criteria , 2016, Alzheimer's & Dementia.
[41] S. DeKosky,et al. Post-mortem correlates of in vivo PiB-PET amyloid imaging in a typical case of Alzheimer's disease , 2008, Brain : a journal of neurology.
[42] Jonathan Richard Shewchuk,et al. What is a Good Linear Element? Interpolation, Conditioning, and Quality Measures , 2002, IMR.
[43] Moo K. Chung,et al. Weighted Fourier Series Representation and Its Application to Quantifying the Amount of Gray Matter , 2007, IEEE Transactions on Medical Imaging.
[44] Paul M. Thompson,et al. Influence of APOE Genotype on Hippocampal Atrophy over Time - An N=1925 Surface-Based ADNI Study , 2016, PloS one.
[45] Yang Song,et al. Surface-based Tbm Boosts Power to Detect Disease Effects on the Brain: an N = 804 Adni Study ☆ and the Alzheimer's Disease Neuroimaging Initiative , 2022 .
[46] Josephine Barnes,et al. Basic visual function and cortical thickness patterns in posterior cortical atrophy. , 2011, Cerebral cortex.
[47] Amity E. Green,et al. 3D comparison of low, intermediate, and advanced hippocampal atrophy in MCI , 2010, Human brain mapping.
[48] Thomas E. Nichols,et al. Controlling the familywise error rate in functional neuroimaging: a comparative review , 2003, Statistical methods in medical research.
[49] Sébastien Ourselin,et al. Automated voxel-based 3D cortical thickness measurement in a combined Lagrangian-Eulerian PDE approach using partial volume maps , 2009, Medical Image Anal..
[50] Gang Wang,et al. A novel cortical thickness estimation method based on volumetric Laplace-Beltrami operator and heat kernel , 2015, Medical Image Anal..
[51] David A. Boas,et al. Tetrahedral mesh generation from volumetric binary and grayscale images , 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.
[52] Norbert Schuff,et al. Mapping Alzheimer's Disease Progression in 1309 Mri Scans: Power Estimates for Different Inter-scan Intervals ☆ ⁎ and the Alzheimer's Disease Neuroimaging Initiative , 2022 .