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 | 205 | 2021 |
Iterative low-dose CT reconstruction with priors trained by artificial neural network D Wu, K Kim, G El Fakhri, Q Li IEEE transactions on medical imaging 36 (12), 2479-2486, 2017 | 194 | 2017 |
Penalized PET reconstruction using deep learning prior and local linear fitting K Kim, D Wu, K Gong, J Dutta, JH Kim, YD Son, HK Kim, G El Fakhri, Q Li IEEE transactions on medical imaging 37 (6), 1478-1487, 2018 | 157 | 2018 |
A cascaded convolutional neural network for X-ray low-dose CT image denoising D Wu, K Kim, GE Fakhri, Q Li arXiv preprint arXiv:1705.04267, 2017 | 61 | 2017 |
Computationally efficient deep neural network for computed tomography image reconstruction D Wu, K Kim, Q Li Medical physics 46 (11), 4763-4776, 2019 | 49 | 2019 |
Consensus neural network for medical imaging denoising with only noisy training samples D Wu, K Gong, K Kim, X Li, Q Li Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 40 | 2019 |
Feature constrained compressed sensing CT image reconstruction from incomplete data via robust principal component analysis of the database D Wu, L Li, L Zhang Physics in Medicine & Biology 58 (12), 4047, 2013 | 39 | 2013 |
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 70, 101993, 2021 | 35 | 2021 |
A weighted polynomial based material decomposition method for spectral x-ray CT imaging D Wu, L Zhang, X Zhu, X Xu, S Wang Physics in Medicine & Biology 61 (10), 3749, 2016 | 33 | 2016 |
Federated Learning used for predicting outcomes in SARS-COV-2 patients M Flores, I Dayan, H Roth, A Zhong, A Harouni, A Gentili, A Abidin, A Liu, ... Research Square, 2021 | 29 | 2021 |
Stationary computed tomography for space and other resource-constrained environments A Cramer, J Hecla, D Wu, X Lai, T Boers, K Yang, T Moulton, S Kenyon, ... Scientific reports 8 (1), 14195, 2018 | 29 | 2018 |
Severity and consolidation quantification of COVID-19 from CT images using deep learning based on hybrid weak labels D Wu, K Gong, CD Arru, F Homayounieh, B Bizzo, V Buch, H Ren, K Kim, ... IEEE Journal of Biomedical and Health Informatics 24 (12), 3529-3538, 2020 | 27 | 2020 |
Artificial intelligence matches subjective severity assessment of pneumonia for prediction of patient outcome and need for mechanical ventilation: a cohort study S Ebrahimian, F Homayounieh, MABC Rockenbach, P Putha, T Raj, ... Scientific Reports 11 (1), 1-10, 2021 | 26 | 2021 |
Self-supervised dynamic CT perfusion image denoising with deep neural networks D Wu, H Ren, Q Li IEEE Transactions on Radiation and Plasma Medical Sciences 5 (3), 350-361, 2020 | 26 | 2020 |
A multi-center study of COVID-19 patient prognosis using deep learning-based CT image analysis and electronic health records K Gong, D Wu, CD Arru, F Homayounieh, N Neumark, J Guan, V Buch, ... European journal of radiology 139, 109583, 2021 | 24 | 2021 |
A hybrid Monte Carlo model for the energy response functions of X-ray photon counting detectors D Wu, X Xu, L Zhang, S Wang Nuclear Instruments and Methods in Physics Research Section A: Accelerators …, 2016 | 24 | 2016 |
MAPEM-Net: an unrolled neural network for Fully 3D PET image reconstruction K Gong, D Wu, K Kim, J Yang, T Sun, G El Fakhri, Y Seo, Q Li 15th International meeting on fully three-dimensional image reconstruction …, 2019 | 22 | 2019 |
EMnet: an unrolled deep neural network for PET image reconstruction K Gong, D Wu, K Kim, J Yang, G El Fakhri, Y Seo, Q Li Medical Imaging 2019: Physics of Medical Imaging 10948, 1203-1208, 2019 | 20 | 2019 |
End-to-end lung nodule detection in computed tomography D Wu, K Kim, B Dong, GE Fakhri, Q Li Machine Learning in Medical Imaging: 9th International Workshop, MLMI 2018 …, 2018 | 19 | 2018 |
End-to-end abnormality detection in medical imaging D Wu, K Kim, B Dong, Q Li | 18 | 2017 |