| MICCAI multi-atlas labeling beyond the cranial vault–workshop and challenge B Landman, Z Xu, J Igelsias, M Styner, T Langerak, A Klein Proc. MICCAI Multi-Atlas Labeling Beyond Cranial Vault—Workshop Challenge 5, 12, 2015 | 652 | 2015 |
| 3d whole brain segmentation using spatially localized atlas network tiles Y Huo, Z Xu, Y Xiong, K Aboud, P Parvathaneni, S Bao, C Bermudez, ... NeuroImage 194, 105-119, 2019 | 298 | 2019 |
| Synseg-net: Synthetic segmentation without target modality ground truth Y Huo, Z Xu, H Moon, S Bao, A Assad, TK Moyo, MR Savona, ... IEEE transactions on medical imaging 38 (4), 1016-1025, 2018 | 280 | 2018 |
| Adversarial synthesis learning enables segmentation without target modality ground truth Y Huo, Z Xu, S Bao, A Assad, RG Abramson, BA Landman 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 185 | 2018 |
| Evaluation of six registration methods for the human abdomen on clinically acquired CT Z Xu, CP Lee, MP Heinrich, M Modat, D Rueckert, S Ourselin, ... IEEE Transactions on Biomedical Engineering 63 (8), 1563-1572, 2016 | 178 | 2016 |
| Automated quantification of CT patterns associated with COVID-19 from chest CT S Chaganti, P Grenier, A Balachandran, G Chabin, S Cohen, T Flohr, ... Radiology: Artificial Intelligence 2 (4), e200048, 2020 | 169 | 2020 |
| Automatic vertebra labeling in large-scale 3D CT using deep image-to-image network with message passing and sparsity regularization D Yang, T Xiong, D Xu, Q Huang, D Liu, SK Zhou, Z Xu, JH Park, M Chen, ... Information Processing in Medical Imaging: 25th International Conference …, 2017 | 131 | 2017 |
| Efficient multi-atlas abdominal segmentation on clinically acquired CT with SIMPLE context learning Z Xu, RP Burke, CP Lee, RB Baucom, BK Poulose, RG Abramson, ... Medical image analysis 24 (1), 18-27, 2015 | 114 | 2015 |
| Semiautomatically quantified tumor volume using 68Ga-PSMA-11 PET as a biomarker for survival in patients with advanced prostate cancer R Seifert, K Herrmann, J Kleesiek, M Schäfers, V Shah, Z Xu, G Chabin, ... Journal of Nuclear Medicine 61 (12), 1786-1792, 2020 | 108 | 2020 |
| Method and system for artificial intelligence based medical image segmentation SK Zhou, M Chen, H Ding, B Georgescu, MA Gulsun, TS Kim, AP Kiraly, ... US Patent 10,878,219, 2020 | 103 | 2020 |
| UNesT: local spatial representation learning with hierarchical transformer for efficient medical segmentation X Yu, Q Yang, Y Zhou, LY Cai, R Gao, HH Lee, T Li, S Bao, Z Xu, ... Medical Image Analysis 90, 102939, 2023 | 65 | 2023 |
| Less is more: Simultaneous view classification and landmark detection for abdominal ultrasound images Z Xu, Y Huo, JH Park, B Landman, A Milkowski, S Grbic, S Zhou Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 61 | 2018 |
| Splenomegaly segmentation using global convolutional kernels and conditional generative adversarial networks Y Huo, Z Xu, S Bao, C Bermudez, AJ Plassard, J Liu, Y Yao, A Assad, ... Medical Imaging 2018: Image Processing 10574, 45-51, 2018 | 60 | 2018 |
| Deep image-to-image recurrent network with shape basis for automatic vertebra labeling in large-scale 3D CT volumes D Yang, T Xiong, D Xu, SK Zhou, M Chen, XU Zhoubing, D Comaniciu, ... US Patent App. 10/366,491, 2019 | 58* | 2019 |
| Deep image-to-image recurrent network with shape basis learning for automatic vertebra labeling in large-scale 3D CT volumes D Yang, T Xiong, D Xu, SK Zhou, Z Xu, M Chen, JH Park, S Grbic, TD Tran, ... Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 57 | 2017 |
| Deep learning based bone removal in computed tomography angiography M Chen, TS Kim, J Kretschmer, S Seifert, SK Zhou, M Schöbinger, D Liu, ... US Patent 10,582,907, 2020 | 52 | 2020 |
| Splenomegaly Segmentation on Multi-Modal MRI Using Deep Convolutional Networks Y Huo, Z Xu, S Bao, C Bermudez, H Moon, P Parvathaneni, TK Moyo, ... IEEE transactions on medical imaging 38 (5), 1185-1196, 2018 | 50 | 2018 |
| Spatially localized atlas network tiles enables 3D whole brain segmentation from limited data Y Huo, Z Xu, K Aboud, P Parvathaneni, S Bao, C Bermudez, SM Resnick, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 48 | 2018 |
| Immersive virtual reality for visualization of abdominal CT Q Lin, Z Xu, B Li, R Baucom, B Poulose, BA Landman, RE Bodenheimer Medical Imaging 2013: Image perception, observer performance, and technology …, 2013 | 45 | 2013 |
| Adversarial and dual inverse deep learning networks for medical image analysis SK Zhou, M Chen, D Xu, XU Zhoubing, D Yang US Patent 10,636,141, 2020 | 43 | 2020 |
Bennett Allan LandmanElectrical and Computer Engineering, Vanderbilt UniversityEmail confirmado em vanderbilt.edu
