Estimating and accounting for the effect of MRI scanner changes on longitudinal whole-brain volume change measurements
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Hyunwoo Lee | Kunio Nakamura | Douglas L. Arnold | Sridar Narayanan | Robert A. Brown | D. Arnold | Kunio Nakamura | S. Narayanan | Robert A. Brown | Hyunwoo Lee
[1] Nick C Fox,et al. The clinical use of structural MRI in Alzheimer disease , 2010, Nature Reviews Neurology.
[2] R. Rudick,et al. Gray matter atrophy in multiple sclerosis: A longitudinal study , 2008, Annals of neurology.
[3] Nick C Fox,et al. A longitudinal study of brain volume changes in normal aging using serial registered magnetic resonance imaging. , 2003, Archives of neurology.
[4] Osamu Abe,et al. Effects of gradient non‐linearity correction and intensity non‐uniformity correction in longitudinal studies using structural image evaluation using normalization of atrophy (SIENA) , 2010, Journal of magnetic resonance imaging : JMRI.
[5] Nick C Fox,et al. Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2 , 2015, Alzheimer's & Dementia.
[6] D. Reich,et al. Volumetric Analysis from a Harmonized Multisite Brain MRI Study of a Single Subject with Multiple Sclerosis , 2017, American Journal of Neuroradiology.
[7] Anders M. Dale,et al. Reliability of MRI-derived measurements of human cerebral cortical thickness: The effects of field strength, scanner upgrade and manufacturer , 2006, NeuroImage.
[8] Rohit Bakshi,et al. Handling changes in MRI acquisition parameters in modeling whole brain lesion volume and atrophy data in multiple sclerosis subjects: Comparison of linear mixed-effect models , 2015, NeuroImage: Clinical.
[9] Garrett M. Fitzmaurice,et al. A Primer in Longitudinal Data Analysis , 2008, Circulation.
[10] Stephen M. Smith,et al. Accurate, Robust, and Automated Longitudinal and Cross-Sectional Brain Change Analysis , 2002, NeuroImage.
[11] C. Jack,et al. Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers , 2013, The Lancet Neurology.
[12] Mark W. Woolrich,et al. Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.
[13] Clifford R Jack,et al. Common MRI acquisition non-idealities significantly impact the output of the boundary shift integral method of measuring brain atrophy on serial MRI , 2006, NeuroImage.
[14] Kunio Nakamura,et al. Segmentation of brain magnetic resonance images for measurement of gray matter atrophy in multiple sclerosis patients , 2009, NeuroImage.
[15] Nick C. Fox,et al. Longitudinal and cross-sectional analysis of atrophy in Alzheimer's disease: Cross-validation of BSI, SIENA and SIENAX , 2007, NeuroImage.
[16] M. Gatz,et al. The Alzheimer's disease knowledge test. , 1988, The Gerontologist.
[17] Owen Carmichael,et al. Update on the Magnetic Resonance Imaging core of the Alzheimer's Disease Neuroimaging Initiative , 2010, Alzheimer's & Dementia.
[18] Russell T. Shinohara,et al. Harmonization of cortical thickness measurements across scanners and sites , 2017, NeuroImage.
[19] C. Jack,et al. Alzheimer's Disease Neuroimaging Initiative , 2008 .
[20] Richard Frayne,et al. Reliability of neuroanatomical measurements in a multisite longitudinal study of youth at risk for psychosis , 2014, Human brain mapping.
[21] D. Louis Collins,et al. BEaST: Brain extraction based on nonlocal segmentation technique , 2012, NeuroImage.
[22] Sankar K. Pal,et al. Segmentation of Brain Magnetic Resonance Images , 2012 .
[23] Jessica A. Turner,et al. Impact of scanner hardware and imaging protocol on image quality and compartment volume precision in the ADNI cohort , 2010, NeuroImage.
[24] C. Almli,et al. Unbiased nonlinear average age-appropriate brain templates from birth to adulthood , 2009, NeuroImage.
[25] Cristina Granziera,et al. Effects of MRI scan acceleration on brain volume measurement consistency , 2012, Journal of magnetic resonance imaging : JMRI.
[26] M. Weissman,et al. Statistical harmonization corrects site effects in functional connectivity measurements from multi‐site fMRI data , 2018, Human brain mapping.
[27] D. Louis Collins,et al. Diurnal fluctuations in brain volume: Statistical analyses of MRI from large populations , 2015, NeuroImage.
[28] C. Crainiceanu,et al. Quantification of multiple-sclerosis-related brain atrophy in two heterogeneous MRI datasets using mixed-effects modeling☆ , 2013, NeuroImage: Clinical.
[29] Alan C. Evans,et al. A nonparametric method for automatic correction of intensity nonuniformity in MRI data , 1998, IEEE Transactions on Medical Imaging.
[30] D. Louis Collins,et al. Gradient distortions in MRI: Characterizing and correcting for their effects on SIENA-generated measures of brain volume change , 2010, NeuroImage.
[31] Liguan Wang,et al. A Nonparametric Method for Automatic Denoising of Microseismic Data , 2018, Shock and Vibration.
[32] Anders M. Dale,et al. MRI-derived measurements of human subcortical, ventricular and intracranial brain volumes: Reliability effects of scan sessions, acquisition sequences, data analyses, scanner upgrade, scanner vendors and field strengths , 2009, NeuroImage.
[33] Sebastien Ourselin,et al. Cerebral atrophy in mild cognitive impairment and Alzheimer disease , 2013, Neurology.
[34] F. Barkhof,et al. Grey Matter Atrophy in Multiple Sclerosis: Clinical Interpretation Depends on Choice of Analysis Method , 2016, PloS one.
[35] Owen Carmichael,et al. Standardization of analysis sets for reporting results from ADNI MRI data , 2013, Alzheimer's & Dementia.
[36] Russell T. Shinohara,et al. Harmonization of cortical thickness measurements across scanners and sites , 2017 .
[37] S. Aoki,et al. Magnetic resonance , 2012, International Journal of Computer Assisted Radiology and Surgery.
[38] J. Blass,et al. Volume changes in Alzheimer's disease and mild cognitive impairment: cognitive associations , 2010 .