Tae Hyung Kim
Tae Hyung Kim
Martinos Center, Massachusetts General Hospital, Harvard Medical School
Geverifieerd e-mailadres voor mgh.harvard.edu - Homepage
Titel
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Jaar
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
462018
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
422017
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
302018
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
202013
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
152019
LORAKS Software Version 2.0: Faster Implementation and Enhanced Capabilities
TH Kim, JP Haldar
USC-SIPI Technical Report, 443, 2018
152018
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
142018
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
142017
LORAKI: Autocalibrated recurrent neural networks for autoregressive MRI reconstruction in k-space
TH Kim, P Garg, JP Haldar
arXiv preprint arXiv:1904.09390, 2019
132019
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
132015
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
62017
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, 2019
52019
Learning-based computational MRI reconstruction without big data: from linear interpolation and structured low-rank matrices to recurrent neural networks
TH Kim, JP Haldar
Wavelets and Sparsity XVIII 11138, 1113817, 2019
32019
Efficient iterative solutions to complex-valued nonlinear least-squares problems with mixed linear and antilinear operators
TH Kim, JP Haldar
Optimization and Engineering, 1-20, 2021
12021
Learning How to Interpolate Fourier Data With Unknown Autoregressive Structure: An Ensemble-Based Approach
TH Kim, JP Haldar
2019 53rd Asilomar Conference on Signals, Systems, and Computers, 1471-1475, 2019
2019
Simultaneous Multi-slice MRI Reconstruction using LORAKS
TH Kim, JP Haldar
Proc. Intl. Soc. Mag. Reson. Med 23, 0078, 2015
2015
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Artikelen 1–16