| Deep convolutional neural networks for computer-aided detection: CNN architectures, dataset characteristics and transfer learning HC Shin, HR Roth, M Gao, L Lu, Z Xu, I Nogues, J Yao, D Mollura, ... IEEE transactions on medical imaging 35 (5), 1285-1298, 2016 | 6446 | 2016 |
| Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets SA Harmon, TH Sanford, S Xu, EB Turkbey, H Roth, Z Xu, D Yang, ... Nature communications 11 (1), 4080, 2020 | 629 | 2020 |
| Monai: An open-source framework for deep learning in healthcare MJ Cardoso, W Li, R Brown, N Ma, E Kerfoot, Y Wang, B Murrey, ... arXiv preprint arXiv:2211.02701, 2022 | 622 | 2022 |
| Generalizing deep learning for medical image segmentation to unseen domains via deep stacked transformation L Zhang, X Wang, D Yang, T Sanford, S Harmon, B Turkbey, BJ Wood, ... IEEE transactions on medical imaging 39 (7), 2531-2540, 2020 | 477 | 2020 |
| A review on segmentation of positron emission tomography images B Foster, U Bagci, A Mansoor, Z Xu, DJ Mollura Computers in biology and medicine 50, 76-96, 2014 | 451 | 2014 |
| Standardized assessment of automatic segmentation of white matter hyperintensities and results of the WMH segmentation challenge HJ Kuijf, JM Biesbroek, J De Bresser, R Heinen, S Andermatt, M Bento, ... IEEE transactions on medical imaging 38 (11), 2556-2568, 2019 | 337 | 2019 |
| Segmentation and image analysis of abnormal lungs at CT: current approaches, challenges, and future trends A Mansoor, U Bagci, B Foster, Z Xu, GZ Papadakis, LR Folio, JK Udupa, ... Radiographics 35 (4), 1056-1076, 2015 | 333 | 2015 |
| When radiology report generation meets knowledge graph Y Zhang, X Wang, Z Xu, Q Yu, A Yuille, D Xu Proceedings of the AAAI conference on artificial intelligence 34 (07), 12910 …, 2020 | 328 | 2020 |
| Holistic classification of CT attenuation patterns for interstitial lung diseases via deep convolutional neural networks M Gao, U Bagci, L Lu, A Wu, M Buty, HC Shin, H Roth, GZ Papadakis, ... Computer Methods in Biomechanics and Biomedical Engineering: Imaging …, 2018 | 310 | 2018 |
| Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japan D Yang, Z Xu, W Li, A Myronenko, HR Roth, S Harmon, S Xu, B Turkbey, ... Medical image analysis 70, 101992, 2021 | 278 | 2021 |
| CT-Realistic Lung Nodule Simulation from 3D Conditional Generative Adversarial Networks for Robust Lung Segmentation D Jin, Z Xu, Y Tang, AP Harrison, DJ Mollura Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 2 …, 2018 | 232 | 2018 |
| A generic approach to pathological lung segmentation A Mansoor, U Bagci, Z Xu, B Foster, KN Olivier, JM Elinoff, AF Suffredini, ... IEEE transactions on medical imaging 33 (12), 2293-2310, 2014 | 209 | 2014 |
| Joint segmentation of anatomical and functional images: Applications in quantification of lesions from PET, PET-CT, MRI-PET, and MRI-PET-CT images U Bagci, JK Udupa, N Mendhiratta, B Foster, Z Xu, J Yao, X Chen, ... Medical image analysis 17 (8), 929-945, 2013 | 207 | 2013 |
| Federated learning improves site performance in multicenter deep learning without data sharing KV Sarma, S Harmon, T Sanford, HR Roth, Z Xu, J Tetreault, D Xu, ... Journal of the American Medical Informatics Association 28 (6), 1259-1264, 2021 | 194 | 2021 |
| Progressive and multi-path holistically nested neural networks for pathological lung segmentation from CT images AP Harrison, Z Xu, K George, L Lu, RM Summers, DJ Mollura International Conference on Medical Image Computing and Computer-Assisted …, 2017 | 161 | 2017 |
| Mycobacterium tuberculosis dysregulates MMP/TIMP balance to drive rapid cavitation and unrestrained bacterial proliferation A Kübler, B Luna, C Larsson, NC Ammerman, BB Andrade, M Orandle, ... The Journal of pathology 235 (3), 431-444, 2015 | 128 | 2015 |
| Capsules for biomedical image segmentation R LaLonde, Z Xu, I Irmakci, S Jain, U Bagci Medical image analysis 68, 101889, 2021 | 111 | 2021 |
| Interactive segmentation of medical images through fully convolutional neural networks T Sakinis, F Milletari, H Roth, P Korfiatis, P Kostandy, K Philbrick, Z Akkus, ... arXiv preprint arXiv:1903.08205, 2019 | 110 | 2019 |
| Nvidia flare: Federated learning from simulation to real-world HR Roth, Y Cheng, Y Wen, I Yang, Z Xu, YT Hsieh, K Kersten, A Harouni, ... arXiv preprint arXiv:2210.13291, 2022 | 105 | 2022 |
| Deep vessel tracking: A generalized probabilistic approach via deep learning A Wu, Z Xu, M Gao, M Buty, DJ Mollura 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 1363-1367, 2016 | 96 | 2016 |
Holger R. RothNVIDIAEmail được xác minh tại nvidia.com