| Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 233 | 2018 |
| Extraction of dynamic functional connectivity from brain grey matter and white matter for MCI classification X Chen, H Zhang, L Zhang, C Shen, SW Lee, D Shen Human brain mapping 38 (10), 5019-5034, 2017 | 79 | 2017 |
| Deep embedding convolutional neural network for synthesizing CT image from T1-Weighted MR image L Xiang, Q Wang, D Nie, L Zhang, X Jin, Y Qiao, D Shen Medical image analysis 47, 31-44, 2018 | 56 | 2018 |
| Automatic labeling of MR brain images by hierarchical learning of atlas forests L Zhang, Q Wang, Y Gao, G Wu, D Shen Medical physics 43 (3), 1175-1186, 2016 | 24 | 2016 |
| Concatenated spatially-localized random forests for hippocampus labeling in adult and infant MR brain images L Zhang, Q Wang, Y Gao, H Li, G Wu, D Shen Neurocomputing 229, 3-12, 2017 | 21 | 2017 |
| Learning-based structurally-guided construction of resting-state functional correlation tensors L Zhang, H Zhang, X Chen, Q Wang, PT Yap, D Shen Magnetic resonance imaging 43, 110-121, 2017 | 15 | 2017 |
| Brain atlas fusion from high-thickness diagnostic magnetic resonance images by learning-based super-resolution J Zhang, L Zhang, L Xiang, Y Shao, G Wu, X Zhou, D Shen, Q Wang Pattern recognition 63, 531-541, 2017 | 15 | 2017 |
| Brain image labeling using multi-atlas guided 3D fully convolutional networks L Fang, L Zhang, D Nie, X Cao, K Bahrami, H He, D Shen International Workshop on Patch-based Techniques in Medical Imaging, 12-19, 2017 | 9 | 2017 |
| Automatic Brain Labeling via Multi-Atlas Guided Fully Convolutional Networks L Fang, L Zhang, D Nie, X Cao, I Rekik, SW Lee, H He, D Shen Medical Image Analysis, 2018 | 7 | 2018 |
| Learning of atlas forest hierarchy for automatic labeling of MR brain images L Zhang, Q Wang, Y Gao, G Wu, D Shen International Workshop on Machine Learning in Medical Imaging, 323-330, 2014 | 6 | 2014 |
| Reflection component separation using statistical analysis and polarisation L Zhang, ER Hancock, GA Atkinson Iberian Conference on Pattern Recognition and Image Analysis, 476-483, 2011 | 6 | 2011 |
| Multi-atlas context forests for knee MR image segmentation Q Liu, Q Wang, L Zhang, Y Gao, D Shen International Workshop on Machine Learning in Medical Imaging, 186-193, 2015 | 5 | 2015 |
| Robust estimation of shape and polarisation using blind source separation L Zhang, ER Hancock Pattern Recognition Letters 34 (8), 856-862, 2013 | 5 | 2013 |
| Exploring diagnosis and imaging biomarkers of Parkinson’s disease via iterative canonical correlation analysis based feature selection L Liu, Q Wang, E Adeli, L Zhang, H Zhang, D Shen Computerized Medical Imaging and Graphics 67, 21-29, 2018 | 4 | 2018 |
| Functional MRI registration with tissue‐specific patch‐based functional correlation tensors Y Zhou, H Zhang, L Zhang, X Cao, R Yang, Q Feng, PT Yap, D Shen Human brain mapping 39 (6), 2303-2316, 2018 | 4 | 2018 |
| Feature selection based on iterative canonical correlation analysis for automatic diagnosis of Parkinson’s disease L Liu, Q Wang, E Adeli, L Zhang, H Zhang, D Shen International Conference on Medical Image Computing and Computer-Assisted …, 2016 | 4 | 2016 |
| A comprehensive polarisation model for surface orientation recovery L Zhang, ER Hancock Proceedings of the 21st International Conference on Pattern Recognition …, 2012 | 4 | 2012 |
| Resting-state network complexity and magnitude changes in neonates with severe hypoxic ischemic encephalopathy HX Li, M Yu, AB Zheng, QF Zhang, GW Hua, WJ Tu, LC Zhang Neural regeneration research 14 (4), 642, 2019 | 3 | 2019 |
| Feature‐shared adaptive‐boost deep learning for invasiveness classification of pulmonary subsolid nodules in CT images J Wang, X Chen, H Lu, L Zhang, J Pan, Y Bao, J Su, D Qian Medical Physics 47 (4), 1738-1749, 2020 | 2 | 2020 |
| Segmentation and Classification in Digital Pathology for Glioma Research: Challenges and Deep Learning Approaches T Kurc, S Bakas, X Ren, A Bagari, A Momeni, Y Huang, L Zhang, A Kumar, ... Frontiers in Neuroscience 14, 2020 | 2 | 2020 |
Dinggang ShenJ. H. Distinguished Investigator; Professor of Radiology; Director, Center for Image Analysis andVerified email at med.unc.edu
