| Low-dose CT image denoising using a generative adversarial network with Wasserstein distance and perceptual loss Q Yang, P Yan, Y Zhang, H Yu, Y Shi, X Mou, MK Kalra, Y Zhang, L Sun, ... IEEE transactions on medical imaging 37 (6), 1348-1357, 2018 | 1404 | 2018 |
| 3-D convolutional encoder-decoder network for low-dose CT via transfer learning from a 2-D trained network H Shan, Y Zhang, Q Yang, U Kruger, MK Kalra, L Sun, W Cong, G Wang IEEE transactions on medical imaging 37 (6), 1522-1534, 2018 | 452 | 2018 |
| Structurally-sensitive multi-scale deep neural network for low-dose CT denoising C You, Q Yang, H Shan, L Gjesteby, G Li, S Ju, Z Zhang, Z Zhao, Y Zhang, ... IEEE access 6, 41839-41855, 2018 | 232 | 2018 |
| Spectral CT reconstruction with image sparsity and spectral mean Y Zhang, Y Xi, Q Yang, W Cong, J Zhou, G Wang IEEE transactions on computational imaging 2 (4), 510-523, 2016 | 118 | 2016 |
| Deep learning methods to guide CT image reconstruction and reduce metal artifacts L Gjesteby, Q Yang, Y Xi, Y Zhou, J Zhang, G Wang Medical Imaging 2017: Physics of Medical Imaging 10132, 752-758, 2017 | 111 | 2017 |
| Deep learning methods for CT image-domain metal artifact reduction L Gjesteby, Q Yang, Y Xi, H Shan, B Claus, Y Jin, B De Man, G Wang Developments in X-ray Tomography XI 10391, 147-152, 2017 | 92 | 2017 |
| CT image denoising with perceptive deep neural networks Q Yang, P Yan, MK Kalra, G Wang arXiv preprint arXiv:1702.07019, 2017 | 86 | 2017 |
| Tomographic image reconstruction via machine learning G Wang, W Cong, Y Qingsong US Patent 10,970,887, 2021 | 68 | 2021 |
| Vision 20/20: Simultaneous CT‐MRI—Next chapter of multimodality imaging G Wang, M Kalra, V Murugan, Y Xi, L Gjesteby, M Getzin, Q Yang, ... Medical physics 42 (10), 5879-5889, 2015 | 61 | 2015 |
| A dual-stream deep convolutional network for reducing metal streak artifacts in CT images L Gjesteby, H Shan, Q Yang, Y Xi, Y Jin, D Giantsoudi, H Paganetti, ... Physics in Medicine & Biology 64 (23), 235003, 2019 | 53 | 2019 |
| Reducing metal streak artifacts in CT images via deep learning: Pilot results L Gjesteby, Q Yang, Y Xi, B Claus, Y Jin, B De Man, G Wang The 14th international meeting on fully three-dimensional image …, 2017 | 53 | 2017 |
| Dynamic bowtie filter for cone-beam/multi-slice CT F Liu, Q Yang, W Cong, G Wang PloS one 9 (7), e103054, 2014 | 45 | 2014 |
| Deep neural network for CT metal artifact reduction with a perceptual loss function L Gjesteby, H Shan, Q Yang, Y Xi, B Claus, Y Jin, B De Man, G Wang The fifth international conference on image formation in X-ray computed …, 2018 | 40 | 2018 |
| CT image reconstruction on a low dimensional manifold W Cong, G Wang, Q Yang, J Li, J Hsieh, R Lai Inverse problems and imaging (Springfield, Mo.) 13 (3), 449, 2019 | 19 | 2019 |
| Hybrid imaging system for simultaneous spiral MR and X-ray (MRX) scans L Gjesteby, Y Xi, MK Kalra, Q Yang, G Wang IEEE Access 5, 1050-1061, 2016 | 19 | 2016 |
| Superiorization-based multi-energy CT image reconstruction Q Yang, W Cong, G Wang Inverse problems 33 (4), 044014, 2017 | 17 | 2017 |
| Spectral X-ray CT image reconstruction with a combination of energy-integrating and photon-counting detectors Q Yang, W Cong, Y Xi, G Wang PloS one 11 (5), e0155374, 2016 | 17 | 2016 |
| Attenuation map reconstruction from TOF PET data G Wang, W Cong, Y Qingsong US Patent 9,600,910, 2017 | 14 | 2017 |
| Big Data from CT Scanning GW Qingsong Yang, Mannudeep K. Kalra, Atul Padole , Jia Li , Elizabeth ... JSciMed Central® Journal 2 (1), 1003, 2015 | 11* | 2015 |
| Attenuation map reconstruction from TOF PET data G Wang, Y Qingsong, W Cong US Patent 10,537,299, 2020 | 9 | 2020 |
Ge WangRensselaer Polytechnic InstituteZweryfikowany adres z rpi.edu
