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• Kim Dong-Hyun, Choi Seung-Hong, Park Sung-Hong

• Investigative Magnetic Resonance Imaging   2020  Volume.24  No.4 241 ~ 251

• A Self-Supervised Learning Framework for Under-Sampling Pattern Design Using Graph Convolution Netwo...

• Li Yuze

• Chen Huijun

• Investigative Magnetic Resonance Imaging   2020  Volume.24  No.4 232 ~ 240

• Unsupervised Deformable Image Registration Using Polyphase UNet for 3D Brain MRI Volumes

• Martin Antoinette D.

• Kim Bo-Ah, Ye Jong-Chul

• Investigative Magnetic Resonance Imaging   2020  Volume.24  No.4 223 ~ 231

• Cascaded Residual Dense Networks for Dynamic MR Imaging with Edge-Enhanced Loss Constraint

• Ke Ziwen

• Zhu Yanjie, Liang Dong

• Investigative Magnetic Resonance Imaging   2020  Volume.24  No.4 214 ~ 222

• Exploring Generalization Capacity of Artificial Neural Network for Myelin Water Imaging

• Lee Ji-Eun

• Choi Joon-Yul, Shin Dong-Myung, Kim Eung-Yeop, Oh Se-Hong, Lee Jong-Ho

• Investigative Magnetic Resonance Imaging   2020  Volume.24  No.4 207 ~ 213

• Deep Learning in MR Motion Correction: a Brief Review and a New Motion Simulation Tool (view2Dmotion...

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• Jung Soo-Zy, Jung Kyu-Jin, Kim Dong-Hyun

• Investigative Magnetic Resonance Imaging   2020  Volume.24  No.4 196 ~ 206

• A Comparative Study of Unsupervised Deep Learning Methods for MRI Reconstruction

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• Quan Cong, Wang Siyuan, Zhu Yuanzheng, Zhang Minghui, Zhu Yanjie, Liu Qiegen

• Investigative Magnetic Resonance Imaging   2020  Volume.24  No.4 179 ~ 195