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Biblio
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2023
Homssi M
,
Sweeney EM
,
Demmon E
,
Mannheim W
,
Sakirsky M
,
Wang Y
,
Gauthier SA
,
Gupta A
,
Nguyen TD
. 2023.
Evaluation of the Statistical Detection of Change Algorithm for Screening Patients with MS with New Lesion Activity on Longitudinal Brain MRI.
.
AJNR Am J Neuroradiol. 44(6):649-655.
Lin M
,
Li T
,
Yang Y
,
Holste G
,
Ding Y
,
Van Tassel SH
,
Kovacs K
,
Shih G
,
Wang Z
,
Lu Z
et al.
. 2023.
Improving model fairness in image-based computer-aided diagnosis.
.
Nat Commun. 14(1):6261.
Wu G
,
Cheligeer C
,
Brisson A-M
,
Quan MLynn
,
Cheung WY
,
Brenner D
,
Lupichuk S
,
Teman C
,
Basmadjian RBarkev
,
Popwich B
et al.
. 2023.
A New Method of Identifying Pathologic Complete Response After Neoadjuvant Chemotherapy for Breast Cancer Patients Using a Population-Based Electronic Medical Record System.
.
Ann Surg Oncol. 30(4):2095-2103.
Dimov AV
,
Li J
,
Nguyen TD
,
Roberts AG
,
Spincemaille P
,
Straub S
,
Zun Z
,
Prince MR
,
Wang Y
. 2023.
QSM Throughout the Body.
.
J Magn Reson Imaging. 57(6):1621-1640.
2022
Bae J
,
Huang Z
,
Knoll F
,
Geras K
,
Sood TPandit
,
Feng L
,
Heacock L
,
Moy L
,
Kim SGene
. 2022.
Estimation of the capillary level input function for dynamic contrast-enhanced MRI of the breast using a deep learning approach.
.
Magn Reson Med. 87(5):2536-2550.
Dimov AV
,
Nguyen TD
,
Spincemaille P
,
Sweeney EM
,
Zinger N
,
Kovanlikaya I
,
Kopell BH
,
Gauthier SA
,
Wang Y
. 2022.
Global cerebrospinal fluid as a zero-reference regularization for brain quantitative susceptibility mapping.
.
J Neuroimaging. 32(1):141-147.
2021
Zhang H
,
Zhang J
,
Li C
,
Sweeney EM
,
Spincemaille P
,
Nguyen TD
,
Gauthier SA
,
Wang Y
,
Marcille M
. 2021.
ALL-Net: Anatomical information lesion-wise loss function integrated into neural network for multiple sclerosis lesion segmentation.
.
Neuroimage Clin. 32:102854.
Parker DB
,
Spincemaille P
,
Razlighi QR
. 2021.
Attenuation of motion artifacts in fMRI using discrete reconstruction of irregular fMRI trajectories (DRIFT).
.
Magn Reson Med. 86(3):1586-1599.
Jafari R
,
Spincemaille P
,
Zhang J
,
Nguyen TD
,
Luo X
,
Cho J
,
Margolis D
,
Prince MR
,
Wang Y
. 2021.
Deep neural network for water/fat separation: Supervised training, unsupervised training, and no training.
.
Magn Reson Med. 85(4):2263-2277.
Gu Z
,
Jamison KWakefield
,
Sabuncu MRory
,
Kuceyeski A
. 2021.
Heritability and interindividual variability of regional structure-function coupling.
.
Nat Commun. 12(1):4894.
Akerele MI
,
Karakatsanis NA
,
Forsythe RO
,
Dweck MR
,
Syed M
,
Aykroyd RG
,
Sourbron S
,
Newby DE
,
Tsoumpas C
. 2021.
Iterative reconstruction incorporating background correction improves quantification of [F]-NaF PET/CT images of patients with abdominal aortic aneurysm.
.
J Nucl Cardiol. 28(5):1875-1886.
Wen Y
,
Spincemaille P
,
Nguyen T
,
Cho J
,
Kovanlikaya I
,
Anderson J
,
Wu G
,
Yang B
,
Fung M
,
Li K
et al.
. 2021.
Multiecho complex total field inversion method (mcTFI) for improved signal modeling in quantitative susceptibility mapping.
.
Magn Reson Med. 86(4):2165-2178.
2020
Han D
,
Shah S
,
Lee JHyun
,
Elmore K
,
Gransar H
,
Danad I
,
Kumar V
,
Raman S
,
Hartaigh BÓ
,
Dunham S
et al.
. 2020.
An approach to evaluate myocardial perfusion defect assessment for projection-based DECT: A phantom study.
.
Clin Imaging. 63:10-15.
Liu Z
,
Wen Y
,
Spincemaille P
,
Zhang S
,
Yao Y
,
Nguyen TD
,
Wang Y
. 2020.
Automated adaptive preconditioner for quantitative susceptibility mapping.
.
Magn Reson Med. 83(1):271-285.
Ma Y
,
Sun H
,
Cho J
,
Mazerolle EL
,
Wang Y
,
G Pike B
. 2020.
Cerebral OEF quantification: A comparison study between quantitative susceptibility mapping and dual-gas calibrated BOLD imaging.
.
Magn Reson Med. 83(1):68-82.
Cho J
,
Zhang S
,
Kee Y
,
Spincemaille P
,
Nguyen TD
,
Hubertus S
,
Gupta A
,
Wang Y
. 2020.
Cluster analysis of time evolution (CAT) for quantitative susceptibility mapping (QSM) and quantitative blood oxygen level-dependent magnitude (qBOLD)-based oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO ) mapping.
.
Magn Reson Med. 83(3):844-857.
Bao Q
,
Ma L
,
Liberman G
,
Solomon E
,
Martinho RP
,
Frydman L
. 2020.
Dynamic T mapping by multi-spin-echo spatiotemporal encoding.
.
Magn Reson Med. 84(2):895-907.
Bao Q
,
Liberman G
,
Solomon E
,
Frydman L
. 2020.
High-resolution diffusion MRI studies of development in pregnant mice visualized by novel spatiotemporal encoding schemes.
.
NMR Biomed. 33(3):e4208.
2019
Lee H-H
,
Yaros K
,
Veraart J
,
Pathan JL
,
Liang F-X
,
Kim SG
,
Novikov DS
,
Fieremans E
. 2019.
Along-axon diameter variation and axonal orientation dispersion revealed with 3D electron microscopy: implications for quantifying brain white matter microstructure with histology and diffusion MRI.
.
Brain Struct Funct. 224(4):1469-1488.
Zhang S
,
Liu Z
,
Nguyen TD
,
Yao Y
,
Gillen KM
,
Spincemaille P
,
Kovanlikaya I
,
Gupta A
,
Wang Y
. 2019.
Clinical feasibility of brain quantitative susceptibility mapping.
.
Magn Reson Imaging. 60:44-51.
Zhang J
,
Kim SGene
. 2019.
Estimation of cellular-interstitial water exchange in dynamic contrast enhanced MRI using two flip angles.
.
NMR Biomed. 32(11):e4135.
Wen Y
,
Weinsaft JW
,
Nguyen TD
,
Liu Z
,
Horn EM
,
Singh H
,
Kochav J
,
Eskreis-Winkler S
,
Deh K
,
Kim J
et al.
. 2019.
Free breathing three-dimensional cardiac quantitative susceptibility mapping for differential cardiac chamber blood oxygenation - initial validation in patients with cardiovascular disease inclusive of direct comparison to invasive catheterization.
.
J Cardiovasc Magn Reson. 21(1):70.
Deidda D
,
Karakatsanis NA
,
Robson PM
,
Calcagno C
,
Senders ML
,
Mulder WJM
,
Fayad ZA
,
Aykroyd RG
,
Tsoumpas C
. 2019.
Hybrid PET/MR Kernelised Expectation Maximisation Reconstruction for Improved Image-Derived Estimation of the Input Function from the Aorta of Rabbits.
.
Contrast Media Mol Imaging. 2019:3438093.
Zhuang M
,
Karakatsanis NA
,
Dierckx RAJO
,
Zaidi H
. 2019.
Impact of Tissue Classification in MRI-Guided Attenuation Correction on Whole-Body Patlak PET/MRI.
.
Mol Imaging Biol. 21(6):1147-1156.
Khosla M
,
Jamison K
,
Ngo GH
,
Kuceyeski A
,
Sabuncu MR
. 2019.
Machine learning in resting-state fMRI analysis.
.
Magn Reson Imaging. 64:101-121.
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