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BUDA-SAGE with self-supervised denoising enables fast, distortion-free, high-resolution T2, T2*, para- and dia-magnetic susceptibility mapping

Sep 09, 2021
Zijing Zhang, Long Wang, Jaejin Cho, Congyu Liao, Hyeong-Geol Shin, Xiaozhi Cao, Jongho Lee, Jinmin Xu, Tao Zhang, Huihui Ye, Kawin Setsompop, Huafeng Liu, Berkin Bilgic

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DeepRF: Deep Reinforcement Learning Designed RadioFrequency Waveform in MRI

May 07, 2021
Dongmyung Shin, Younghoon Kim, Chungseok Oh, Hongjun An, Juhyung Park, Jiye Kim, Jongho Lee

* 35 pages, 5 figures, 1 table 

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DIFFnet: Diffusion parameter mapping network generalized for input diffusion gradient schemes and bvalues

Feb 04, 2021
Juhung Park, Woojin Jung, Eun-Jung Choi, Se-Hong Oh, Dongmyung Shin, Hongjun An, Jongho Lee

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Machine-Learning Approach to Analyze the Status of Forklift Vehicles with Irregular Movement in a Shipyard

Oct 12, 2020
Hyeonju Lee, Jongho Lee, Minji An, Gunil Park, Sungchul Choi

* I withdraw this paper because an error in the experiment has been found 

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Deep Reinforcement Learning Designed RF Pulse: $DeepRF_{SLR}$

Dec 19, 2019
Dongmyung Shin, Sooyeon Ji, Doohee Lee, Jieun Lee, Se-Hong Oh, Jongho Lee

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Nonlinear Dipole Inversion (NDI) enables Quantitative Susceptibility Mapping (QSM) without parameter tuning

Sep 30, 2019
Daniel Polak, Itthi Chatnuntawech, Jaeyeon Yoon, Siddharth Srinivasan Iyer, Jongho Lee, Peter Bachert, Elfar Adalsteinsson, Kawin Setsompop, Berkin Bilgic

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