| Deep learning in medical image analysis D Shen, G Wu, HI Suk Annual review of biomedical engineering 19 (1), 221-248, 2017 | 4624 | 2017 |
| Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis HI Suk, SW Lee, D Shen, Alzheimer's Disease Neuroimaging Initiative NeuroImage 101, 569-582, 2014 | 979 | 2014 |
| Deep learning based imaging data completion for improved brain disease diagnosis R Li, W Zhang, HI Suk, L Wang, J Li, D Shen, S Ji Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014 | 581 | 2014 |
| Latent feature representation with stacked auto-encoder for AD/MCI diagnosis HI Suk, SW Lee, D Shen, Alzheimer’s Disease Neuroimaging Initiative Brain Structure and Function 220, 841-859, 2015 | 579 | 2015 |
| Deep learning-based feature representation for AD/MCI classification HI Suk, D Shen Medical Image Computing and Computer-Assisted Intervention–MICCAI 2013: 16th …, 2013 | 554 | 2013 |
| State-space model with deep learning for functional dynamics estimation in resting-state fMRI HI Suk, CY Wee, SW Lee, D Shen NeuroImage 129, 292-307, 2016 | 331 | 2016 |
| Deep ensemble learning of sparse regression models for brain disease diagnosis HI Suk, SW Lee, D Shen, Alzheimer’s Disease Neuroimaging Initiative Medical image analysis 37, 101-113, 2017 | 301 | 2017 |
| A novel Bayesian framework for discriminative feature extraction in brain-computer interfaces HI Suk, SW Lee IEEE Transactions on Pattern Analysis and Machine Intelligence 35 (2), 286-299, 2012 | 253 | 2012 |
| Hand gesture recognition based on dynamic Bayesian network framework HI Suk, BK Sin, SW Lee Pattern recognition 43 (9), 3059-3072, 2010 | 249 | 2010 |
| A novel relational regularization feature selection method for joint regression and classification in AD diagnosis X Zhu, HI Suk, L Wang, SW Lee, D Shen, ... Medical image analysis 38, 205-214, 2017 | 241 | 2017 |
| A novel matrix-similarity based loss function for joint regression and classification in AD diagnosis X Zhu, HI Suk, D Shen NeuroImage 100, 91-105, 2014 | 226 | 2014 |
| Subspace regularized sparse multitask learning for multiclass neurodegenerative disease identification X Zhu, HI Suk, SW Lee, D Shen IEEE Transactions on Biomedical Engineering 63 (3), 607-618, 2015 | 220 | 2015 |
| Deep sparse multi-task learning for feature selection in Alzheimer’s disease diagnosis HI Suk, SW Lee, D Shen, Alzheimer’s Disease Neuroimaging Initiative Brain Structure and Function 221, 2569-2587, 2016 | 176 | 2016 |
| Commanding a brain-controlled wheelchair using steady-state somatosensory evoked potentials KT Kim, HI Suk, SW Lee IEEE Transactions on Neural Systems and Rehabilitation Engineering 26 (3 …, 2016 | 148 | 2016 |
| Person authentication from neural activity of face-specific visual self-representation SK Yeom, HI Suk, SW Lee Pattern recognition 46 (4), 1159-1169, 2013 | 141 | 2013 |
| Multimodal manifold-regularized transfer learning for MCI conversion prediction B Cheng, M Liu, HI Suk, D Shen, D Zhang Brain imaging and behavior 9 (4), 913-926, 2015 | 111 | 2015 |
| Non-homogeneous spatial filter optimization for ElectroEncephaloGram (EEG)-based motor imagery classification TE Kam, HI Suk, SW Lee Neurocomputing 108, 58-68, 2013 | 111 | 2013 |
| Machine Learning in Medical Imaging: 9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings Y Shi, HI Suk, M Liu Springer, 2018 | 107 | 2018 |
| Canonical feature selection for joint regression and multi-class identification in Alzheimer’s disease diagnosis X Zhu, HI Suk, SW Lee, D Shen Brain imaging and behavior 10, 818-828, 2016 | 103 | 2016 |
| Subject and class specific frequency bands selection for multiclass motor imagery classification HI Suk, SW Lee International Journal of Imaging Systems and Technology 21 (2), 123-130, 2011 | 101 | 2011 |
Dinggang ShenProf. and Founding Dean, School of BME, ShanghaiTech University; Co-CEO, United Imaging Intelligenceshanghaitech.edu.cn의 이메일 확인됨
