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Tae Hyung Kim
Tae Hyung Kim
Assistant Professor, Computer Engineering, Hongik University
Verified email at hongik.ac.kr - Homepage
Title
Cited by
Cited by
Year
Improving parallel imaging by jointly reconstructing multi‐contrast data
B Bilgic, TH Kim, C Liao, MK Manhard, LL Wald, JP Haldar, K Setsompop
Magnetic resonance in medicine 80 (2), 619-632, 2018
952018
LORAKS makes better SENSE: phase‐constrained partial fourier SENSE reconstruction without phase calibration
TH Kim, K Setsompop, JP Haldar
Magnetic resonance in medicine 77 (3), 1021-1035, 2017
792017
LORAKI: Autocalibrated recurrent neural networks for autoregressive MRI reconstruction in k-space
TH Kim, P Garg, JP Haldar
arXiv preprint arXiv:1904.09390, 2019
592019
Navigator-free EPI ghost correction with structured low-rank matrix models: New theory and methods
RA Lobos, TH Kim, WS Hoge, JP Haldar
IEEE transactions on medical imaging 37 (11), 2390-2402, 2018
542018
Wave‐LORAKS: Combining wave encoding with structured low‐rank matrix modeling for more highly accelerated 3D imaging
TH Kim, B Bilgic, D Polak, K Setsompop, JP Haldar
Magnetic resonance in medicine 81 (3), 1620-1633, 2019
402019
Analyzing incentives for protocol compliance in complex domains: A case study of introduction-based routing
MP Wellman, TH Kim, Q Duong
arXiv preprint arXiv:1306.0388, 2013
272013
LORAKS Software Version 2.0: Faster Implementation and Enhanced Capabilities
TH Kim, JP Haldar
USC-SIPI Technical Report, 443, 2018
252018
The Fourier radial error spectrum plot: A more nuanced quantitative evaluation of image reconstruction quality
TH Kim, JP Haldar
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), 61-64, 2018
212018
SMS-LORAKS: Calibrationless simultaneous multislice MRI using low-rank matrix modeling
TH Kim, JP Haldar
2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 323-326, 2015
162015
Navigator-free EPI ghost correction using low-rank matrix modeling: Theoretical insights and practical improvements
RA Lobos, TH Kim, WS Hoge, JP Haldar
Proc. Int. Soc. Magn. Reson. Med, 0449, 2017
152017
Wave-encoded model-based deep learning for highly accelerated imaging with joint reconstruction
J Cho, B Gagoski, TH Kim, Q Tian, R Frost, I Chatnuntawech, B Bilgic
Bioengineering 9 (12), 736, 2022
102022
Current perspectives of biodegradable drug-eluting stents for improved safety
SJ Kim, TH Kim, JW Choi, IK Kwon
Biotechnology and bioprocess engineering 17, 912-924, 2012
102012
Time‐efficient, high‐resolution 3T whole‐brain relaxometry using 3D‐QALAS with wave‐CAIPI readouts
J Cho, B Gagoski, TH Kim, F Wang, MK Manhard, D Dean III, ...
Magnetic Resonance in Medicine 91 (2), 630-639, 2024
8*2024
High-fidelity mesoscale in-vivo diffusion MRI through gSlider-BUDA and circular EPI with S-LORAKS reconstruction
C Liao, U Yarach, X Cao, SS Iyer, N Wang, TH Kim, Q Tian, B Bilgic, ...
Neuroimage 275, 120168, 2023
82023
Computational imaging with LORAKS: Reconstructing linearly predictable signals using low-rank matrix regularization
JP Haldar, TH Kim
2017 51st Asilomar Conference on Signals, Systems, and Computers, 1870-1874, 2017
82017
LORAKI: Reconstruction of undersampled k-space data using scan-specific autocalibrated recurrent neural networks
TH Kim, P Garg, JP Haldar
Proc. Int. Soc. Magn. Reson. Med 4647, 50-63, 2019
72019
Scan-specific recurrent neural network for image reconstruction
TH Kim, J Haldar
US Patent 11,710,261, 2023
62023
Wave-LORAKS for faster wave-CAIPI MRI
TH Kim, B Bilgic, D Polak, K Setsompop, JP Haldar
Proc. Int. Soc. Magn. Reson. Med 25, 1037, 2017
62017
Joint MAPLE: Accelerated joint T1 and T2* mapping with scan-specific self-supervised networks
A Heydari, A Ahmadi, TH Kim, B Bilgic
Magnetic resonance in medicine 91 (6), 2294-2309, 2024
42024
High‐fidelity, high‐spatial‐resolution diffusion magnetic resonance imaging of ex vivo whole human brain at ultra‐high gradient strength with structured low‐rank echo‐planar …
G Ramos‐Llordén, RA Lobos, TH Kim, Q Tian, T Witzel, HH Lee, A Scholz, ...
NMR in Biomedicine 36 (2), e4831, 2023
42023
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