ExploreASL: An image processing pipeline for multi-center ASL perfusion MRI studies
暂无分享,去创建一个
Liesbeth Reneman | Frederik Barkhof | Xavier Golay | David L. Thomas | Mario Masellis | Michael A. Chappell | Pieter Vandemaele | Alle Meije Wink | Jeroen de Bresser | Fernando Zelaya | Hugo Kuijf | Matthias Günther | Jeroen Hendrikse | Jan Petr | Matthan W.A. Caan | Saima Hilal | Eric Achten | Silvia Ingala | Edo Richard | Iris Asllani | Zahra Shirzadi | Anouk Schrantee | Inge Groote | Joost P.A. Kuijer | Atle Bjørnerud | Astrid Bjørnebekk | Henri Mutsaerts | Paul Groot | Andrew D Robertson | Lena Václavů | Owen O’Daly | Ilse Kant | Catherine Morgan | Elisabeth Lysvik | Patricia Clement | Udunna C. Anazodo | Dasja Pajkrt | Reinoud P.H. Bokkers | Bradley J. MacIntosh | Matthias J.P. van Osch | Enrico de Vita | Aart Nederveen | David L. Thomas | F. Barkhof | X. Golay | J. Kuijer | A. Bjørnerud | O. O'Daly | M. Chappell | F. Zelaya | E. de Vita | E. Achten | J. Hendrikse | M. V. van Osch | J. de Bresser | B. MacIntosh | A. Wink | P. Vandemaele | M. Caan | E. Richard | M. Masellis | A. Nederveen | L. Reneman | M. Günther | I. Asllani | Andrew Donald Robertson | A. Schrantee | I. Groote | H. Mutsaerts | S. Hilal | A. Bjørnebekk | D. Pajkrt | H. Kuijf | Zahra Shirzadi | R. Bokkers | S. Ingala | U. Anazodo | J. Petr | H. Mutsaerts | Patricia Clement | L. Václavů | Paul Groot | Catherine A. Morgan | Ilse M. J. Kant | E. Lysvik | J. de Bresser
[1] Lutz Tellmann,et al. Comparison of cerebral blood flow acquired by simultaneous [15O]water positron emission tomography and arterial spin labeling magnetic resonance imaging , 2014, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[2] P Jezzard,et al. Partial volume correction of multiple inversion time arterial spin labeling MRI data , 2011, Magnetic resonance in medicine.
[3] S. Black,et al. Temporal and Spatial Variances in Arterial Spin-Labeling Are Inversely Related to Large-Artery Blood Velocity , 2017, American Journal of Neuroradiology.
[4] Rose.,et al. 谁对谁错——Who Is Correct? , 2009 .
[5] Thomas E. Nichols,et al. Best practices in data analysis and sharing in neuroimaging using MRI , 2017, Nature Neuroscience.
[6] Thomas M Seed,et al. Acute Effects , 2011 .
[7] J. Gilmore,et al. Infant Brain Atlases from Neonates to 1- and 2-Year-Olds , 2011, PloS one.
[8] J. Detre,et al. Potentials and Challenges for Arterial Spin Labeling in Pharmacological Magnetic Resonance Imaging , 2011, Journal of Pharmacology and Experimental Therapeutics.
[9] Sébastien Ourselin,et al. Scale Factor Point Spread Function Matching: Beyond Aliasing in Image Resampling , 2015, MICCAI.
[10] Thomas T. Liu,et al. Cerebral Blood Flow Measurements in Adults: A Review on the Effects of Dietary Factors and Exercise , 2018, Nutrients.
[11] D. Weinberger,et al. Noise reduction in 3D perfusion imaging by attenuating the static signal in arterial spin tagging (ASSIST) , 2000, Magnetic resonance in medicine.
[12] C. Gaser,et al. Partial Volume Segmentation with Adaptive Maximum A Posteriori (MAP) Approach , 2009, NeuroImage.
[13] D. Selkoe. Alzheimer's disease. , 2011, Cold Spring Harbor perspectives in biology.
[14] Thomas E. Nichols,et al. Scanning the horizon: towards transparent and reproducible neuroimaging research , 2016, Nature Reviews Neuroscience.
[15] Yang Li,et al. ASL‐MRICloud: An online tool for the processing of ASL MRI data , 2019, NMR in biomedicine.
[16] John A Butman,et al. Reduced distortion artifact whole brain CBF mapping using blip-reversed non-segmented 3D echo planar imaging with pseudo-continuous arterial spin labeling. , 2017, Magnetic resonance imaging.
[17] Gerard R. Ridgway,et al. Symmetric Diffeomorphic Modeling of Longitudinal Structural MRI , 2013, Front. Neurosci..
[18] Sina Aslan,et al. On the sensitivity of ASL MRI in detecting regional differences in cerebral blood flow. , 2010, Magnetic resonance imaging.
[19] Peiying Liu,et al. Fast measurement of blood T1 in the human carotid artery at 3T: Accuracy, precision, and reproducibility , 2017, Magnetic resonance in medicine.
[20] J. Detre,et al. Reduced Transit-Time Sensitivity in Noninvasive Magnetic Resonance Imaging of Human Cerebral Blood Flow , 1996, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[21] John Ashburner,et al. A fast diffeomorphic image registration algorithm , 2007, NeuroImage.
[22] Adnan Bibic,et al. Denoising of arterial spin labeling data: wavelet-domain filtering compared with Gaussian smoothing , 2010, Magnetic Resonance Materials in Physics, Biology and Medicine.
[23] John Ashburner,et al. SPM: A history , 2012, NeuroImage.
[24] Matthias Günther,et al. Correction for Susceptibility Distortions Increases the Performance of Arterial Spin Labeling in Patients with Cerebrovascular Disease , 2016, Journal of neuroimaging : official journal of the American Society of Neuroimaging.
[25] Esben Thade Petersen,et al. Partial volume correction of brain perfusion estimates using the inherent signal data of time‐resolved arterial spin labeling , 2014, NMR in biomedicine.
[26] D. Louis Collins,et al. Brain templates and atlases , 2012, NeuroImage.
[27] Carmen E Sanchez,et al. Age-Specific MRI Templates for Pediatric Neuroimaging , 2012, Developmental neuropsychology.
[28] Thomas T. Liu,et al. Physiological noise reduction for arterial spin labeling functional MRI , 2006, NeuroImage.
[29] John A. Detre,et al. Comparison of 2D and 3D single-shot ASL perfusion fMRI sequences , 2013, NeuroImage.
[30] Fenella J Kirkham,et al. Arterial spin labeling characterization of cerebral perfusion during normal maturation from late childhood into adulthood: normal ‘reference range' values and their use in clinical studies , 2014, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[31] T. Brown,et al. Regression algorithm correcting for partial volume effects in arterial spin labeling MRI , 2008, Magnetic resonance in medicine.
[32] Xiaoyun Liang,et al. Voxel-Wise Functional Connectomics Using Arterial Spin Labeling Functional Magnetic Resonance Imaging: The Role of Denoising , 2015, Brain Connect..
[33] Xia Li,et al. Errors in Quantitative Image Analysis due to Platform-Dependent Image Scaling. , 2014, Translational oncology.
[34] Matthias Günther,et al. Separation of macrovascular signal in multi‐inversion time arterial spin labelling MRI , 2010, Magnetic resonance in medicine.
[35] Nick C Fox,et al. Secondary prevention of Alzheimer’s dementia: neuroimaging contributions , 2018, Alzheimer's Research & Therapy.
[36] Karl J. Friston,et al. Spatial Normalization Nonlinear Spatial Normalization Using Basis Functions Spatial Normalization Spatial Normalization Spatial Normalization Spatial Normalization Spatial Normalization Spatial Normalization Spatial Normalization 2.1 the Basic Optimization Algorithm 1 C a from This We Can Derive an , 1999 .
[37] S. Black,et al. Automated removal of spurious intermediate cerebral blood flow volumes improves image quality among older patients: A clinical arterial spin labeling investigation , 2015, Journal of magnetic resonance imaging : JMRI.
[38] Nick C Fox,et al. Secondary prevention of Alzheimer’s dementia: neuroimaging contributions , 2018, Alzheimer's Research & Therapy.
[39] D. Alsop,et al. Continuous flow‐driven inversion for arterial spin labeling using pulsed radio frequency and gradient fields , 2008, Magnetic resonance in medicine.
[40] A. Connelly,et al. Improved partial volume correction for single inversion time arterial spin labeling data , 2013, Magnetic resonance in medicine.
[41] Rolf Pohmann,et al. Accurate, localized quantification of white matter perfusion with single‐voxel ASL , 2010, Magnetic resonance in medicine.
[42] Alan C. Evans,et al. Fast and robust parameter estimation for statistical partial volume models in brain MRI , 2004, NeuroImage.
[43] Jennifer L. Whitwell,et al. Accurate automatic estimation of total intracranial volume: A nuisance variable with less nuisance , 2015, NeuroImage.
[44] Amir Alansary,et al. MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans , 2015, Comput. Intell. Neurosci..
[45] Karl J. Friston,et al. Spatial normalization of lesioned brains: Performance evaluation and impact on fMRI analyses , 2007, NeuroImage.
[46] Georg Schramm,et al. Partial volume correction in arterial spin labeling using a Look‐Locker sequence , 2013, Magnetic Resonance in Medicine.
[47] R. Wang,et al. Assessment of cerebral blood flow in Alzheimer's disease by continuous arterial spin labeling MR imaging , 2008 .
[48] J Mazziotta,et al. A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[49] Thomas Dierks,et al. Auditory verbal hallucinations: imaging, analysis, and intervention , 2012, European Archives of Psychiatry and Clinical Neuroscience.
[50] Marion Smits,et al. Effects of systematic partial volume errors on the estimation of gray matter cerebral blood flow with arterial spin labeling MRI , 2018, Magnetic Resonance Materials in Physics, Biology and Medicine.
[51] C. Iadecola,et al. SUMO2/3 is Associated with Ubiquitinated Protein Aggregates in the Mouse Neocortex after Middle Cerebral Artery Occlusion , 2015, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[52] R. Wiest,et al. Variability of physiological brain perfusion in healthy subjects – A systematic review of modifiers. Considerations for multi-center ASL studies , 2017, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[53] Peter Reiss,et al. Higher subcortical and white matter cerebral blood flow in perinatally HIV-infected children , 2017, Medicine.
[54] Owen Carmichael,et al. Update on the Magnetic Resonance Imaging core of the Alzheimer's Disease Neuroimaging Initiative , 2010, Alzheimer's & Dementia.
[55] Max A. Viergever,et al. elastix: A Toolbox for Intensity-Based Medical Image Registration , 2010, IEEE Transactions on Medical Imaging.
[56] J. Detre,et al. Structural Correlation‐based Outlier Rejection (SCORE) algorithm for arterial spin labeling time series , 2017, Journal of magnetic resonance imaging : JMRI.
[57] Ze Wang,et al. Empirical optimization of ASL data analysis using an ASL data processing toolbox: ASLtbx. , 2008, Magnetic resonance imaging.
[58] Ze Wang,et al. Support vector machine learning‐based cerebral blood flow quantification for arterial spin labeling MRI , 2014, Human brain mapping.
[59] Michael A. Chappell,et al. Introduction to Perfusion Quantification using Arterial Spin Labelling , 2018 .
[60] Bernhard Hemmer,et al. An automated tool for detection of FLAIR-hyperintense white-matter lesions in Multiple Sclerosis , 2012, NeuroImage.
[61] P. Mitra,et al. The Brain Atlas Concordance Problem: Quantitative Comparison of Anatomical Parcellations , 2009, PloS one.
[62] L. D. de Vries,et al. Impact of neonate haematocrit variability on the longitudinal relaxation time of blood: Implications for arterial spin labelling MRI , 2014, NeuroImage: Clinical.
[63] Bruce Fischl,et al. Accurate and robust brain image alignment using boundary-based registration , 2009, NeuroImage.
[64] Veronica Redaelli,et al. Cerebral perfusion changes in presymptomatic genetic frontotemporal dementia: a GENFI study , 2019, Brain : a journal of neurology.
[65] M. Weissman,et al. Test-retest reliability of cerebral blood flow in healthy individuals using arterial spin labeling: Findings from the EMBARC study. , 2018, Magnetic resonance imaging.
[66] C. Zimmer,et al. Quantification of blood flow in brain tumors: comparison of arterial spin labeling and dynamic susceptibility-weighted contrast-enhanced MR imaging. , 2003, Radiology.
[67] R Nick Bryan,et al. Comparison of non-invasive MRI measurements of cerebral blood flow in a large multisite cohort , 2016, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[68] John Duncan,et al. Implementation and application of a brain template for multiple volumes of interest , 2002, Human brain mapping.
[69] Aart J. Nederveen,et al. Accuracy and precision of pseudo-continuous arterial spin labeling perfusion during baseline and hypercapnia: A head-to-head comparison with 15O H2O positron emission tomography , 2014, NeuroImage.
[70] A J Nederveen,et al. In Vivo T1 of Blood Measurements in Children with Sickle Cell Disease Improve Cerebral Blood Flow Quantification from Arterial Spin-Labeling MRI , 2016, American Journal of Neuroradiology.
[71] G. Zaharchuk,et al. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: A consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. , 2015, Magnetic resonance in medicine.
[72] O B Paulson,et al. Quantitation of Regional Cerebral Blood Flow Corrected for Partial Volume Effect Using O-15 Water and PET: II. Normal Values and Gray Matter Blood Flow Response to Visual Activation , 2000, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[73] Eileen Luders,et al. A 12-step user guide for analyzing voxel-wise gray matter asymmetries in statistical parametric mapping (SPM) , 2015, Nature Protocols.
[74] Michael Schär,et al. Cardiac‐triggered pseudo‐continuous arterial‐spin‐labeling: A cost‐effective scheme to further enhance the reliability of arterial‐spin‐labeling MRI , 2018, Magnetic resonance in medicine.
[75] Christopher Rorden,et al. The first step for neuroimaging data analysis: DICOM to NIfTI conversion , 2016, Journal of Neuroscience Methods.
[76] Scott Holland,et al. CerebroMatic: A Versatile Toolbox for Spline-Based MRI Template Creation , 2017, Front. Comput. Neurosci..
[77] 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.
[78] F. X. Aymerich,et al. Lesion filling effect in regional brain volume estimations: a study in multiple sclerosis patients with low lesion load , 2016, Neuroradiology.
[79] Kristian Bredies,et al. Spatio-temporal TGV denoising for ASL perfusion imaging , 2017, NeuroImage.
[80] Bojana Stefanovic,et al. Enhancement of automated blood flow estimates (ENABLE) from arterial spin‐labeled MRI , 2018, Journal of magnetic resonance imaging : JMRI.
[81] P T Fox,et al. Perfusion‐weighted imaging of interictal hypoperfusion in temporal lobe epilepsy using FAIR‐HASTE: Comparison with H215O PET measurements , 2001, Magnetic resonance in medicine.
[82] Josep Marco-Pallarés,et al. Analysis of automated methods for spatial normalization of lesioned brains , 2012, NeuroImage.
[83] Aart J Nederveen,et al. The spatial coefficient of variation in arterial spin labeling cerebral blood flow images , 2017, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[84] Karl J. Friston,et al. Diffeomorphic registration using geodesic shooting and Gauss–Newton optimisation , 2011, NeuroImage.
[85] Stefan Skare,et al. How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging , 2003, NeuroImage.
[86] Donald S. Williams,et al. Perfusion imaging , 1992, Magnetic resonance in medicine.
[87] José Luis Molinuevo,et al. Development of interventions for the secondary prevention of Alzheimer's dementia: the European Prevention of Alzheimer's Dementia (EPAD) project. , 2016, The lancet. Psychiatry.
[88] Abraham Z. Snyder,et al. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion , 2012, NeuroImage.
[89] Sebastien Ourselin,et al. Comparison of arterial spin labeling registration strategies in the multi‐center GENetic frontotemporal dementia initiative (GENFI) , 2018, Journal of magnetic resonance imaging : JMRI.
[90] David H. Miller,et al. Reducing the impact of white matter lesions on automated measures of brain gray and white matter volumes , 2010, Journal of magnetic resonance imaging : JMRI.
[91] Esben Thade Petersen,et al. Improved calculation of the equilibrium magnetization of arterial blood in arterial spin labeling , 2018, Magnetic resonance in medicine.
[92] Egill Rostrup,et al. Phase contrast mapping MRI measurements of global cerebral blood flow across different perfusion states – A direct comparison with 15O-H2O positron emission tomography using a hybrid PET/MR system , 2018, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[93] R. Wirestam,et al. Accuracy of Parenchymal Cerebral Blood Flow Measurements Using Pseudocontinuous Arterial Spin-Labeling in Healthy Volunteers , 2015, American Journal of Neuroradiology.
[94] E Bezak,et al. Evaluation of current clinical target volume definitions for glioblastoma using cell-based dosimetry stochastic methods. , 2015, The British journal of radiology.
[95] Ze Wang,et al. Arterial spin labeling perfusion MRI signal denoising using robust principal component analysis , 2018, Journal of Neuroscience Methods.
[96] H. Beaumont,et al. Multimodal Magnetic Resonance Imaging of Frontotemporal Lobar Degeneration , 2015 .
[97] Arno Klein,et al. Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration , 2009, NeuroImage.
[98] A ChappellMichael,et al. Variational Bayesian inference for a nonlinear forward model , 2009 .
[99] Jeroen Hendrikse,et al. Intra- and Multicenter Reproducibility of Pulsed, Continuous and Pseudo-Continuous Arterial Spin Labeling Methods for Measuring Cerebral Perfusion , 2011, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[100] Atholl Johnston,et al. Acute effects of single‐dose aripiprazole and haloperidol on resting cerebral blood flow (rCBF) in the human brain , 2013, Human brain mapping.
[101] Fernando Zelaya,et al. ASAP (Automatic Software for ASL Processing): A toolbox for processing Arterial Spin Labeling images. , 2016, Magnetic resonance imaging.
[102] Yaakov Stern,et al. Separating function from structure in perfusion imaging of the aging brain , 2009, Human brain mapping.
[103] Marion Smits,et al. Early-stage differentiation between presenile Alzheimer’s disease and frontotemporal dementia using arterial spin labeling MRI , 2015, European Radiology.
[104] Alan Connelly,et al. Reduction of errors in ASL cerebral perfusion and arterial transit time maps using image de‐noising , 2010, Magnetic resonance in medicine.
[105] Toralf Mildner,et al. Characterization of pseudo‐continuous arterial spin labeling: Simulations and experimental validation , 2018, Magnetic resonance in medicine.
[106] Karl J. Friston,et al. Statistical parametric mapping (SPM) , 2008, Scholarpedia.
[107] Daniel Gallichan,et al. Measuring the Effects of Remifentanil on Cerebral Blood Flow and Arterial Arrival Time Using 3D Grase MRI with Pulsed Arterial Spin Labelling , 2008, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[108] Yi Wang,et al. Multi-vendor reliability of arterial spin labeling perfusion MRI using a near-identical sequence: Implications for multi-center studies , 2015, NeuroImage.
[109] R. Kraft,et al. Arterial Spin-Labeling in Routine Clinical Practice, Part 1: Technique and Artifacts , 2008, American Journal of Neuroradiology.
[110] S. Francis,et al. Consensus-based technical recommendations for clinical translation of renal ASL MRI , 2019, Magnetic Resonance Materials in Physics, Biology and Medicine.
[111] Mechthild Krause,et al. Photon vs. proton radiochemotherapy: Effects on brain tissue volume and perfusion. , 2018, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[112] Satrajit S. Ghosh,et al. The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments , 2016, Scientific Data.
[113] David L. Thomas,et al. Evaluation of segmented 3D acquisition schemes for whole‐brain high‐resolution arterial spin labeling at 3 T , 2014, NMR in biomedicine.
[114] M. Battaglini,et al. Evaluating and reducing the impact of white matter lesions on brain volume measurements , 2012, Human brain mapping.
[115] Woody Sherman,et al. Improved Docking of Polypeptides with Glide , 2013, J. Chem. Inf. Model..
[116] Josef Pfeuffer,et al. Comparison of pulsed arterial spin labeling encoding schemes and absolute perfusion quantification. , 2009, Magnetic resonance imaging.
[117] Aart J. Nederveen,et al. Hemodynamic provocation with acetazolamide shows impaired cerebrovascular reserve in adults with sickle cell disease , 2018, Haematologica.
[118] Kim Mouridsen,et al. The QUASAR reproducibility study, Part II: Results from a multi-center Arterial Spin Labeling test–retest study , 2010, NeuroImage.
[119] Raffaella Barone,et al. General Model , 2005, Encyclopedia of Biometrics.
[120] Stephen M Smith,et al. Fast robust automated brain extraction , 2002, Human brain mapping.
[121] Michael A Chappell,et al. Calibration of arterial spin labeling data—potential pitfalls in post‐processing , 2019, Magnetic resonance in medicine.
[122] J. Detre,et al. Noninvasive MRI evaluation of cerebral blood flow in cerebrovascular disease , 1998, Neurology.
[123] J. Ashburner,et al. Nonlinear spatial normalization using basis functions , 1999, Human brain mapping.
[124] A. O. Scott,et al. Planning-free cerebral blood flow territory mapping in patients with intracranial arterial stenosis , 2017, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[125] Peter Jezzard,et al. Assessment of arterial arrival times derived from multiple inversion time pulsed arterial spin labeling MRI , 2010, Magnetic resonance in medicine.
[126] Chun Yuan,et al. Simultaneous measurement of brain perfusion and labeling efficiency in a single pseudo‐continuous arterial spin labeling scan , 2018, Magnetic resonance in medicine.
[127] G. Houston,et al. Diagnostic classification of arterial spin labeling and structural MRI in presenile early stage dementia , 2014, Human brain mapping.
[128] Aart J. Nederveen,et al. Gray matter contamination in arterial spin labeling white matter perfusion measurements in patients with dementia☆ , 2013, NeuroImage: Clinical.
[129] Christian Barillot,et al. Using negative signal in mono-TI pulsed arterial spin labeling to outline pathological increases in arterial transit times , 2012 .
[130] Olivier Salvado,et al. Reproducibility of multiphase pseudo-continuous arterial spin labeling and the effect of post-processing analysis methods , 2015, NeuroImage.
[131] David H. Salat,et al. Age-associated reductions in cerebral blood flow are independent from regional atrophy , 2011, NeuroImage.
[132] Hugo Vrenken,et al. Impact of removing facial features from MR images of MS patients on automatic lesion and atrophy metrics , 2017 .
[133] Ruth Oliver,et al. Improved Quantification of Arterial Spin Labelling Images using Partial Volume Correction Techniques , 2015 .
[134] Karl J. Friston,et al. Unified segmentation , 2005, NeuroImage.
[135] Wiro J. Niessen,et al. IT Infrastructure to Support the Secondary Use of Routinely Acquired Clinical Imaging Data for Research , 2014, Neuroinformatics.
[136] Yufen Chen,et al. Test–retest reliability of arterial spin labeling with common labeling strategies , 2011, Journal of magnetic resonance imaging : JMRI.
[137] Massimo Filippi,et al. Performance of five research-domain automated WM lesion segmentation methods in a multi-center MS study , 2017, NeuroImage.
[138] R. Kraft,et al. A fast, effective filtering method for improving clinical pulsed arterial spin labeling MRI , 2009, Journal of magnetic resonance imaging : JMRI.
[139] Fenella J Kirkham,et al. A general model to calculate the spin-lattice (T1) relaxation time of blood, accounting for haematocrit, oxygen saturation and magnetic field strength , 2016, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[140] Jan Petr,et al. Spatial coefficient of variation of arterial spin labeling MRI as a cerebrovascular correlate of carotid occlusive disease , 2020, PloS one.
[141] Lars T. Westlye,et al. Cerebral blood flow changes after a day of wake, sleep, and sleep deprivation , 2019, NeuroImage.
[142] Thomas T. Liu,et al. The Cerebral Blood Flow Biomedical Informatics Research Network (CBFBIRN) data repository , 2016, NeuroImage.
[143] C. Jack,et al. Alzheimer's Disease Neuroimaging Initiative , 2008 .
[144] Karl J. Friston,et al. Modelling Geometric Deformations in Epi Time Series , 2022 .
[145] David Atkinson,et al. NiftyFit: a Software Package for Multi-parametric Model-Fitting of 4D Magnetic Resonance Imaging Data , 2016, Neuroinformatics.
[146] Aart J. Nederveen,et al. Inter-Vendor Reproducibility of Pseudo-Continuous Arterial Spin Labeling at 3 Tesla , 2014, PloS one.
[147] Robert W. Cox,et al. AFNI: What a long strange trip it's been , 2012, NeuroImage.
[148] Ronald Boellaard,et al. Comparison of Velocity- and Acceleration-Selective Arterial Spin Labeling with [15O]H2O Positron Emission Tomography , 2015, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[149] C. Barillot,et al. Robust estimation of the cerebral blood flow in arterial spin labelling. , 2014, Magnetic resonance imaging.
[150] Irene Tracey,et al. A systematic study of the sensitivity of partial volume correction methods for the quantification of perfusion from pseudo-continuous arterial spin labeling MRI , 2017, NeuroImage.
[151] Ze Wang,et al. Improving cerebral blood flow quantification for arterial spin labeled perfusion MRI by removing residual motion artifacts and global signal fluctuations. , 2012, Magnetic resonance imaging.