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Christopher W Davies-Jenkins
Christopher W Davies-Jenkins
Johns Hopkins Medicine - Department of Radiology and Radiological Science
Verified email at jh.edu
Title
Cited by
Cited by
Year
Frequency drift in MR spectroscopy at 3T
SCN Hui, M Mikkelsen, HJ Zöllner, V Ahluwalia, S Alcauter, L Baltusis, ...
NeuroImage 241, 118430, 2021
282021
Design and characterization of tissue‐mimicking gel phantoms for diffusion kurtosis imaging
ZG Portakal, S Shermer, C Jenkins, E Spezi, T Perrett, N Tuncel, J Phillips
Medical physics 45 (6), 2476-2485, 2018
242018
MRSNet: Metabolite quantification from edited magnetic resonance spectra with convolutional neural networks
M Chandler, C Jenkins, SM Shermer, FC Langbein
arXiv preprint arXiv:1909.03836, 2019
142019
Feasibility and implications of using subject‐specific macromolecular spectra to model short echo time magnetic resonance spectroscopy data
HJ Zöllner, CW Davies‐Jenkins, S Murali‐Manohar, T Gong, SCN Hui, ...
NMR in Biomedicine 36 (3), e4854, 2023
92023
Neurometabolic timecourse of healthy aging
T Gong, SCN Hui, HJ Zöllner, M Britton, Y Song, Y Chen, ...
NeuroImage 264, 119740, 2022
82022
Seeking ground truth for gaba quantification by edited magnetic resonance spectroscopy: Comparative analysis of TARQUIN, LCModel, JMRUI and GANNET
C Jenkins, M Chandler, FC Langbein, SM Shermer
ArXiv. Retrieved from http://arxiv. org/abs/1909.02163 [Google Scholar], 2019
42019
DW-MRS with ultra-strong diffusion gradients
C Jenkins, E Kleban, L Mueller, CJ Evans, U Rudrapanta, D Jones, ...
22020
Quantification of edited magnetic resonance spectroscopy: a comparative phantom based study of analysis methods
C Jenkins, M Chandler, F Langbein, S Shermer
22019
New techniques for quantification of biomarkers and metabolites by magnetic resonance imaging and spectroscopy
CW Jenkins
22019
sLASER and PRESS perform similarly at revealing metabolite‐age correlations at 3 T
SCN Hui, HJ Zöllner, T Gong, KE Hupfeld, AT Gudmundson, ...
Magnetic resonance in medicine 91 (2), 431-442, 2024
12024
Brain Glutathione and GABA+ levels in autistic children
Y Song, KE Hupfeld, CW Davies‐Jenkins, HJ Zöllner, S Murali‐Manohar, ...
Autism Research, 2024
12024
Application of a 1H brain MRS benchmark dataset to deep learning for out-of-voxel artifacts
AT Gudmundson, CW Davies-Jenkins, İ Özdemir, S Murali-Manohar, ...
Imaging Neuroscience 1, 1-15, 2023
1*2023
Continuous automated analysis workflow for MRS studies
HJ Zöllner, CW Davies-Jenkins, EG Lee, TJ Hendrickson, WT Clarke, ...
Journal of Medical Systems 47 (1), 69, 2023
12023
Cohort-mean measured macromolecules lead to more robust linear-combination modeling than subject-specific or parameterized ones
HJ Zöllner, CW Davies-Jenkins, S Murali-Manohar, T Gong, SCN Hui, ...
bioRxiv, 2022.07. 07.499181, 2022
12022
The influence of spectral registration on diffusion-weighted magnetic resonance spectroscopy ADC estimates
CW Jenkins
ISMRM, 2021
12021
Comparison of R1 Mapping Protocols: What are we measuring?
C Jenkins, I Papadopoulos, SM Shermer
arXiv preprint arXiv:1909.12984, 2019
12019
Integrated Short-TE and Hadamard-edited Multi-Sequence (ISTHMUS) for Advanced MRS
SCN Hui, S Murali-Manohar, HJ Zollner, KE Hupfeld, CW Davies-Jenkins, ...
bioRxiv, 2024.02. 15.580516, 2024
2024
Practical considerations of diffusion-weighted MRS with ultra-strong diffusion gradients
CW Davies-Jenkins, A Döring, F Fasano, E Kleban, L Mueller, CJ Evans, ...
Frontiers in Neuroscience 17, 1258408, 2023
2023
Simultaneous multi-transient linear-combination modeling of MRS data improves uncertainty estimation
HJ Zöllner, C Davies-Jenkins, D Simicic, A Tal, J Sulam, G Oeltzschner
bioRxiv, 2023.11. 01.565164, 2023
2023
Metabolite T1 relaxation times differ across the adult lifespan
S Murali-Manohar, AT Gudmundson, KE Hupfeld, HJ Zöllner, SCN Hui, ...
bioRxiv, 2023.01. 06.522927, 2023
2023
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