| Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success JH Thrall, X Li, Q Li, C Cruz, S Do, K Dreyer, J Brink Journal of the American College of Radiology 15 (3), 504-508, 2018 | 462 | 2018 |
| Deep Learning-Based Image Segmentation on Multimodal Medical Imaging Z Guo, X Li, H Huang, N Guo, Q Li IEEE Transactions on Radiation and Plasma Medical Sciences 3 (2), 162-169, 2019 | 232 | 2019 |
| Federated learning for predicting clinical outcomes in patients with COVID-19 I Dayan, HR Roth, A Zhong, A Harouni, A Gentili, AZ Abidin, A Liu, ... Nature medicine 27 (10), 1735-1743, 2021 | 201 | 2021 |
| Sparse representation of whole-brain fMRI signals for identification of functional networks J Lv, X Jiang, X Li, D Zhu, H Chen, T Zhang, S Zhang, X Hu, J Han, ... Medical image analysis 20 (1), 112-134, 2015 | 179 | 2015 |
| Dynamic functional connectomics signatures for characterization and differentiation of PTSD patients X Li, D Zhu, X Jiang, C Jin, X Zhang, L Guo, J Zhang, X Hu, L Li, T Liu Human brain mapping 35 (4), 1761-1778, 2014 | 157 | 2014 |
| Holistic atlases of functional networks and interactions reveal reciprocal organizational architecture of cortical function J Lv, X Jiang, X Li, D Zhu, S Zhang, S Zhao, H Chen, T Zhang, X Hu, ... IEEE Transactions on Biomedical Engineering 62 (4), 1120-1131, 2014 | 148 | 2014 |
| Characterizing and differentiating task-based and resting state fMRI signals via two-stage sparse representations S Zhang, X Li, J Lv, X Jiang, L Guo, T Liu Brain imaging and behavior 10, 21-32, 2016 | 79 | 2016 |
| Medical image segmentation based on multi-modal convolutional neural network: study on image fusion schemes Z Guo, X Li, H Huang, N Guo, Q Li 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 71 | 2018 |
| Characterizing and differentiating brain state dynamics via hidden Markov models J Ou, L Xie, C Jin, X Li, D Zhu, R Jiang, Y Chen, J Zhang, L Li, T Liu Brain topography 28, 666-679, 2015 | 69 | 2015 |
| Sparse representation of HCP grayordinate data reveals novel functional architecture of cerebral cortex X Jiang, X Li, J Lv, T Zhang, S Zhang, L Guo, T Liu Human brain mapping 36 (12), 5301-5319, 2015 | 61 | 2015 |
| Experimental comparisons of sparse dictionary learning and independent component analysis for brain network inference from fMRI data W Zhang, J Lv, X Li, D Zhu, X Jiang, S Zhang, Y Zhao, L Guo, J Ye, D Hu, ... IEEE Transactions on Biomedical Engineering 66 (1), 289-299, 2018 | 58 | 2018 |
| Inferring functional interaction and transition patterns via dynamic bayesian variable partition models J Zhang, X Li, C Li, Z Lian, X Huang, G Zhong, D Zhu, K Li, C Jin, X Hu, ... Human brain mapping 35 (7), 3314-3331, 2014 | 46 | 2014 |
| Consensus Neural Network for Medical Imaging Denoising with Only Noisy Training Samples D Wu, K Gong, K Kim, X Li, Q Li International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 40 | 2019 |
| Modeling 4d fmri data via spatio-temporal convolutional neural networks (st-cnn) Y Zhao, X Li, W Zhang, S Zhao, M Makkie, M Zhang, Q Li, T Liu Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 40 | 2018 |
| The timing and directional connectivity of human frontoparietal and ventral visual attention networks in emotional scene perception D Sabatinelli, DW Frank, TJ Wanger, M Dhamala, BM Adhikari, X Li Neuroscience 277, 229-238, 2014 | 37 | 2014 |
| Characterization of task-free and task-performance brain states via functional connectome patterns X Zhang, L Guo, X Li, T Zhang, D Zhu, K Li, H Chen, J Lv, C Jin, Q Zhao, ... Medical image analysis 17 (8), 1106-1122, 2013 | 37 | 2013 |
| Inferring consistent functional interaction patterns from natural stimulus FMRI data J Sun, X Hu, X Huang, Y Liu, K Li, X Li, J Han, L Guo, T Liu, J Zhang NeuroImage 61 (4), 987-999, 2012 | 37 | 2012 |
| Deep Metric Learning-based Image Retrieval System for Chest Radiograph and its Clinical Applications in COVID-19 A Zhong, X Li, D Wu, H Ren, K Kim, Y Kim, V Buch, N Neumark, B Bizzo, ... Medical Image Analysis, 101993, 2021 | 35 | 2021 |
| Assessing effects of prenatal alcohol exposure using group-wise sparse representation of fMRI data J Lv, X Jiang, X Li, D Zhu, S Zhao, T Zhang, X Hu, J Han, L Guo, Z Li, ... Psychiatry Research: Neuroimaging 233 (2), 254-268, 2015 | 34 | 2015 |
| Atomic dynamic functional interaction patterns for characterization of ADHD J Ou, Z Lian, L Xie, X Li, P Wang, Y Hao, D Zhu, R Jiang, Y Wang, Y Chen, ... Human brain mapping 35 (10), 5262-5278, 2014 | 33 | 2014 |
Tianming LiuDistinguished Research Professor of Computer Science, University of Georgiacs.uga.edu의 이메일 확인됨
