Artificial neural network for myelin water imaging J Lee, D Lee, JY Choi, D Shin, HG Shin, J Lee Magnetic resonance in medicine 83 (5), 1875-1883, 2020 | 45 | 2020 |
Inter-vendor reproducibility of myelin water imaging using a 3D gradient and spin echo sequence LE Lee, E Ljungberg, D Shin, CR Figley, IM Vavasour, A Rauscher, ... Frontiers in neuroscience 12, 854, 2018 | 36 | 2018 |
Deep reinforcement learning-designed radiofrequency waveform in MRI D Shin, Y Kim, C Oh, H An, J Park, J Kim, J Lee Nature Machine Intelligence 3 (11), 985-994, 2021 | 24 | 2021 |
DIFFnet: diffusion parameter mapping network generalized for input diffusion gradient schemes and b-value J Park, W Jung, EJ Choi, SH Oh, J Jang, D Shin, H An, J Lee IEEE Transactions on Medical Imaging 41 (2), 491-499, 2021 | 21 | 2021 |
Deep Reinforcement Learning Designed Shinnar-Le Roux RF Pulse Using Root-Flipping: DeepRFSLR D Shin, S Ji, D Lee, J Lee, SH Oh, J Lee IEEE transactions on medical imaging 39 (12), 4391-4400, 2020 | 13 | 2020 |
DeepResp: Deep learning solution for respiration-induced B0 fluctuation artifacts in multi-slice GRE H An, HG Shin, S Ji, W Jung, S Oh, D Shin, J Park, J Lee NeuroImage 224, 117432, 2021 | 9 | 2021 |
Method to minimize the errors of ai: Quantifying and exploiting uncertainty of deep learning in brain tumor segmentation J Lee, D Shin, SH Oh, H Kim Sensors 22 (6), 2406, 2022 | 8 | 2022 |
DeepRF: Designing an RF pulse using a self-learning machine D Shin, J Lee Proceedings of the 28th Annual Meeting of ISMRM, Sydney, Australia, 0611, 2020 | 7 | 2020 |
Quad-contrast imaging: simultaneous acquisition of four contrast-weighted images (pd-weighted, t₂-weighted, pd-flair and t₂-flair images) with synthetic t₁-weighted image … S Ji, J Jeong, SH Oh, Y Nam, SH Choi, HG Shin, D Shin, W Jung, J Lee IEEE Transactions on Medical Imaging 40 (12), 3617-3626, 2021 | 6 | 2021 |
Deep reinforcement learning designed RF pulse D Shin, S Ji, D Lee, SH Oh, J Lee Proceedings of the 27th Annual Meeting of ISMRM, Montréal, Québec, Canada, 0757, 2019 | 3 | 2019 |
Real-time processing of myelin water imaging using artificial neural network J Lee, D Lee, JY Choi, D Shin, HG Shin, J Lee Proceedings of the 27th Annual Meeting of ISMRM, Montreal, Quebec, Canada, 2019 | 3 | 2019 |
Exploring generalization capacity of artificial neural network for myelin water imaging J Lee, JY Choi, D Shin, EY Kim, SH Oh, J Lee Investigative Magnetic Resonance Imaging 24 (4), 207-213, 2020 | 2 | 2020 |
Generalizing Visual Question Answering from Synthetic to Human-Written Questions via a Chain of QA with a Large Language Model T Kim, Y Cho, H Shin, Y Jo, D Shin arXiv preprint arXiv:2401.06400, 2024 | 1 | 2024 |
Coil2Coil: Self-supervised MR image denoising using phased-array coil images J Park, D Park, HG Shin, EJ Choi, H An, M Kim, D Shin, SY Chun, J Lee arXiv preprint arXiv:2208.07552, 2022 | 1 | 2022 |
Quantitative MT (qMT) imaging of the Whole Brain: Conventional 3D MT vs. 3D EP-vfMT methods SH Oh, D Shin, K Sakaie, D Ontaneda, MJ Lowe ISMRM, 2018 | 1 | 2018 |
Pretraining Vision-Language Model for Difference Visual Question Answering in Longitudinal Chest X-rays Y Cho, T Kim, H Shin, S Cho, D Shin arXiv preprint arXiv:2402.08966, 2024 | | 2024 |
Multi-View Attention Network to Improve Breast Cancer Detection W Tai, PJ Huang, D Shin Medical Imaging with Deep Learning, 2024 | | 2024 |
Fast and accurate sparse-view CBCT reconstruction using meta-learned neural attenuation field and hash-encoding regularization H Shin, T Kim, J Lee, S Chun, S Cho, D Shin arXiv preprint arXiv:2312.01689, 2023 | | 2023 |
Pulmonary abnormality screening on chest x-rays from different machine specifications: a generalized AI-based image manipulation pipeline H Shin, T Kim, J Park, H Raj, MS Jabbar, ZD Abebaw, J Lee, CC Van, ... European radiology experimental 7 (1), 68, 2023 | | 2023 |
MACHINE-INDEPENDENT AI FOR CHEST X-RAY ABNORMALITY CLASSIFICATION H Shin, T Kim, H Raj, MS Jabbar, ZD Abebaw, D Shin Journal of Medical Imaging and Radiation Sciences 54 (3), S12, 2023 | | 2023 |