about
The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI methods.Cardiovascular magnetic resonance phase contrast imagingTechnical Note: Compact three-tesla magnetic resonance imager with high-performance gradients passes ACR image quality and acoustic noise tests.Comparing 3 T and 1.5 T MRI for tracking Alzheimer's disease progression with tensor-based morphometry.HOW DO SPATIAL AND ANGULAR RESOLUTION AFFECT BRAIN CONNECTIVITY MAPS FROM DIFFUSION MRI?Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2Contrast-enhanced carotid MR angiography with commercially available triggering mechanisms and elliptic centric phase encoding.Measurement of MRI scanner performance with the ADNI phantom.Update on the magnetic resonance imaging core of the Alzheimer's disease neuroimaging initiative.Mapping Alzheimer's disease progression in 1309 MRI scans: power estimates for different inter-scan intervals.Intraoperative magnetic resonance imaging findings during deep brain stimulation surgeryBrain beta-amyloid measures and magnetic resonance imaging atrophy both predict time-to-progression from mild cognitive impairment to Alzheimer's diseaseOptimizing power to track brain degeneration in Alzheimer's disease and mild cognitive impairment with tensor-based morphometry: an ADNI study of 515 subjectsSerum cholesterol and variant in cholesterol-related gene CETP predict white matter microstructureConnectivity network measures predict volumetric atrophy in mild cognitive impairment.Diffusion weighted imaging-based maximum density path analysis and classification of Alzheimer's diseaseEffects of changing from non-accelerated to accelerated MRI for follow-up in brain atrophy measurementCognitive reserve and Alzheimer's disease biomarkers are independent determinants of cognitionDoes MRI scan acceleration affect power to track brain change?Accelerated vs. unaccelerated serial MRI based TBM-SyN measurements for clinical trials in Alzheimer's diseaseRich club analysis in the Alzheimer's disease connectome reveals a relatively undisturbed structural core network.Longitudinal stability of MRI for mapping brain change using tensor-based morphometrySteps to standardization and validation of hippocampal volumetry as a biomarker in clinical trials and diagnostic criterion for Alzheimer's disease.Effects of MRI scan acceleration on brain volume measurement consistency.Shapes of the trajectories of 5 major biomarkers of Alzheimer diseaseMeasurements of RF heating during 3.0-T MRI of a pig implanted with deep brain stimulatorMRI-based brain atrophy rates in ADNI phase 2: acceleration and enrichment considerations for clinical trials.Intensity non-uniformity correction using N3 on 3-T scanners with multichannel phased array coils.State of the art: 3T imaging of the membranous labyrinth.Alzheimer's disease neuroimaging initiative: a one-year follow up study using tensor-based morphometry correlating degenerative rates, biomarkers and cognitionAutomatic quality assessment in structural brain magnetic resonance imaging.Gradient pre-emphasis to counteract first-order concomitant fields on asymmetric MRI gradient systems.Magnetization-prepared shells trajectory with automated gradient waveform design.Integrated image reconstruction and gradient nonlinearity correction.Evaluation of classic 2D time-of-flight MR angiography in the depiction of severe carotid stenosis.NonCartesian MR image reconstruction with integrated gradient nonlinearity correction.Comparison of accelerated T1-weighted whole-brain structural-imaging protocols.Magnetic resonance angiography at 3.0 Tesla: initial clinical experience.Partial fourier and parallel MR image reconstruction with integrated gradient nonlinearity correction.A method for correctly setting the rf flip angle.
P50
Q24647259-26638ACC-6477-4E2B-81FA-3223CE84C24DQ26800754-B3A13CE3-20EC-4457-BB83-9A2088BDD1B6Q30362355-A5ECC3B0-EA3B-41B4-A177-F1DE285D56E1Q30476040-3E17EA95-08A9-41E9-A5F0-7F0CE4D88A7CQ30558213-57289660-D54B-437B-8D3C-7ABF3FA4B0A6Q30981669-1D4B0BF0-B57C-475E-ADFF-07A1A78CFE00Q31767766-2B6891DB-C424-4061-9471-30DF66869075Q33483479-F69205F7-2F29-4553-B616-23206C1D4BBFQ33572446-762D1A48-3D97-4FCE-8492-8C29B6CD50BFQ33759240-45F2FA17-9DD8-4887-8CCF-275648886D10Q33941579-9777644E-A7A0-49B6-A8C9-0DE815E32D8CQ34247849-E8D6FAA6-3798-491F-AF02-5AA7016ECD9BQ34271896-87D58503-839A-4254-B618-5C03556FBEAEQ34344559-BB9121C8-AB26-4FB1-8417-F92C8585E3ACQ34770560-07FD5221-A9C1-4F4D-B8DD-4AA9E8C8847FQ34816113-7559DEAE-1140-4E11-9192-EDE8D8F46F25Q34989777-E1955593-4269-4D84-B8A0-E01BE10D4CB8Q34992153-56FD393D-7D23-4473-B28B-A6C592C42F3AQ35219244-C31265A0-B28C-41ED-AE40-B379B61B20ECQ35686223-E73F3D64-CBB8-4AEB-ABDE-202E1F0AE199Q35858721-9088E9ED-D762-4ADD-8741-365CA891CA6FQ35928408-7B49F0CD-8D5F-4B7B-BC34-CDB4BE5CBAC9Q36093127-AAFA415D-DD9A-4A71-98DE-EE2DBACB9295Q36205024-DFAA672B-5684-49F0-81AA-C8111FFD5141Q36677361-73F23EFD-3EB7-4F69-9371-0FF025FF0B90Q36704073-7C363B5C-8C4A-4D2C-AE39-6FE614173985Q36785972-39845BC6-8C5E-43AA-9A14-3D28898EA7B6Q36925699-BF70BE03-A6C7-4EEA-A4B2-EED9338BDF33Q37128221-6555B1BA-621C-4CC5-A4C0-F80999689CBAQ37228160-47BF1692-0787-4385-8E07-5EF124213C5DQ37427402-2326ADB2-3638-4153-94BB-235AA2BF227CQ38379127-5AD77386-2FE4-447E-BEAC-76D77CDBAEC1Q38612140-75BE3FF3-D470-4F7D-BE47-F10DC742DE8AQ39412072-351CD86F-1B5E-4F95-BED3-C9D224CC87D8Q39693197-032AB4D5-9700-4D41-8DC6-2BAFDE767937Q40247284-2C474106-7ECD-4BC5-9FEF-6B4E19641656Q40616978-CDE673F9-A5AF-4D38-BFA4-B46764CB9667Q40699521-E779918F-031C-43B5-ADC3-538905ECF359Q40727420-5852371F-6574-4D62-A1C0-F973E81E0957Q41822972-C66E8EA0-9659-45F4-B5DD-2122C45E4326
P50
description
hulumtues
@sq
researcher
@en
wetenschapper
@nl
հետազոտող
@hy
name
Matt A Bernstein
@ast
Matt A Bernstein
@en
Matt A Bernstein
@es
Matt A Bernstein
@nl
Matt A Bernstein
@sl
type
label
Matt A Bernstein
@ast
Matt A Bernstein
@en
Matt A Bernstein
@es
Matt A Bernstein
@nl
Matt A Bernstein
@sl
prefLabel
Matt A Bernstein
@ast
Matt A Bernstein
@en
Matt A Bernstein
@es
Matt A Bernstein
@nl
Matt A Bernstein
@sl
P106
P108
P21
P2456
P31
P496
0000-0003-3770-0441