Dufan Wu
Dufan Wu
Assistant Professor, Massachusetts General Hospital and Harvard Medical School
Verified email at - Homepage
Cited by
Cited by
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
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
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
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
Computationally efficient deep neural network for computed tomography image reconstruction
D Wu, K Kim, Q Li
Medical physics 46 (11), 4763-4776, 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
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
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
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
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
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
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
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
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
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
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
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
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
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
End-to-end abnormality detection in medical imaging
D Wu, K Kim, B Dong, Q Li
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