| 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 | 437 | 2018 |
| Lung infection quantification of COVID-19 in CT images with deep learning F Shan, Y Gao, J Wang, W Shi, N Shi, M Han, Z Xue, Y Shi arXiv preprint arXiv:2003.04655, 2020 | 203 | 2020 |
| Deformable MR prostate segmentation via deep feature learning and sparse patch matching Y Guo, Y Gao, D Shen IEEE transactions on medical imaging 35 (4), 1077-1089, 2015 | 189 | 2015 |
| LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images L Wang, Y Gao, F Shi, G Li, JH Gilmore, W Lin, D Shen NeuroImage 108, 160-172, 2015 | 188 | 2015 |
| Estimating CT image from MRI data using structured random forest and auto-context model T Huynh, Y Gao, J Kang, L Wang, P Zhang, J Lian, D Shen IEEE transactions on medical imaging 35 (1), 174-183, 2015 | 170 | 2015 |
| Representation learning: a unified deep learning framework for automatic prostate MR segmentation S Liao, Y Gao, A Oto, D Shen International Conference on Medical image computing and computer-assisted …, 2013 | 169 | 2013 |
| Fully convolutional networks for multi-modality isointense infant brain image segmentation D Nie, L Wang, Y Gao, D Shen 2016 IEEE 13Th international symposium on biomedical imaging (ISBI), 1342-1345, 2016 | 168 | 2016 |
| Segmentation of neonatal brain MR images using patch-driven level sets L Wang, F Shi, G Li, Y Gao, W Lin, JH Gilmore, D Shen NeuroImage 84, 141-158, 2014 | 163 | 2014 |
| Estimating CT image from MRI data using 3D fully convolutional networks D Nie, X Cao, Y Gao, L Wang, D Shen Deep Learning and Data Labeling for Medical Applications, 170-178, 2016 | 144 | 2016 |
| Unsupervised deep feature learning for deformable registration of MR brain images G Wu, M Kim, Q Wang, Y Gao, S Liao, D Shen International Conference on Medical Image Computing and Computer-Assisted …, 2013 | 107 | 2013 |
| Detecting anatomical landmarks for fast Alzheimer’s disease diagnosis J Zhang, Y Gao, Y Gao, BC Munsell, D Shen IEEE transactions on medical imaging 35 (12), 2524-2533, 2016 | 96 | 2016 |
| Large-scale screening of covid-19 from community acquired pneumonia using infection size-aware classification F Shi, L Xia, F Shan, B Song, D Wu, Y Wei, H Yuan, H Jiang, Y He, Y Gao, ... Physics in Medicine & Biology, 2021 | 95 | 2021 |
| Integration of sparse multi-modality representation and anatomical constraint for isointense infant brain MR image segmentation L Wang, F Shi, Y Gao, G Li, JH Gilmore, W Lin, D Shen NeuroImage 89, 152-164, 2014 | 94 | 2014 |
| Longitudinal clinical score prediction in Alzheimer's disease with soft-split sparse regression based random forest L Huang, Y Jin, Y Gao, KH Thung, D Shen, ... Neurobiology of aging 46, 180-191, 2016 | 76 | 2016 |
| Prostate segmentation by sparse representation based classification Y Gao, S Liao, D Shen Medical physics 39 (10), 6372-6387, 2012 | 74 | 2012 |
| ASDNet: attention based semi-supervised deep networks for medical image segmentation D Nie, Y Gao, L Wang, D Shen International conference on medical image computing and computer-assisted …, 2018 | 73 | 2018 |
| Sparse patch-based label propagation for accurate prostate localization in CT images S Liao, Y Gao, J Lian, D Shen IEEE transactions on medical imaging 32 (2), 419-434, 2012 | 70 | 2012 |
| Alzheimer's disease diagnosis using landmark-based features from longitudinal structural MR images J Zhang, M Liu, L An, Y Gao, D Shen IEEE journal of biomedical and health informatics 21 (6), 1607-1616, 2017 | 67 | 2017 |
| Dual-sampling attention network for diagnosis of COVID-19 from community acquired pneumonia X Ouyang, J Huo, L Xia, F Shan, J Liu, Z Mo, F Yan, Z Ding, Q Yang, ... IEEE Transactions on Medical Imaging 39 (8), 2595-2605, 2020 | 66 | 2020 |
| Accurate segmentation of CT male pelvic organs via regression-based deformable models and multi-task random forests Y Gao, Y Shao, J Lian, AZ Wang, RC Chen, D Shen IEEE transactions on medical imaging 35 (6), 1532-1543, 2016 | 64 | 2016 |
