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Featured 2020 Journal Article Editorial for “Deep‐Learning Detection of Cancer Metastasis to the Brain on MRI”Sun, Hongfu (2020). Editorial for “Deep‐Learning Detection of Cancer Metastasis to the Brain on MRI”. Journal of Magnetic Resonance Imaging, 52 (4) jmri.27131, 1237-1238. doi: 10.1002/jmri.27131 |
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2019 Journal Article Extracting more for less: multi‐echo MP2RAGE for simultaneous T 1 ‐weighted imaging, T 1 mapping, mapping, SWI, and QSM from a single acquisitionSun, Hongfu, Cleary, Jon O., Glarin, Rebecca, Kolbe, Scott C., Ordidge, Roger J., Moffat, Bradford A. and Pike, G. Bruce (2019). Extracting more for less: multi‐echo MP2RAGE for simultaneous T 1 ‐weighted imaging, T 1 mapping, mapping, SWI, and QSM from a single acquisition. Magnetic Resonance in Medicine, 83 (4) mrm.27975, 1178-1191. doi: 10.1002/mrm.27975 |
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Featured 2018 Journal Article Whole head quantitative susceptibility mapping using a least-norm direct dipole inversion methodSun, Hongfu, Ma, Yuhan, MacDonald, M. Ethan and Pike, G. Bruce (2018). Whole head quantitative susceptibility mapping using a least-norm direct dipole inversion method. NeuroImage, 179, 166-175. doi: 10.1016/j.neuroimage.2018.06.036 |
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Featured 2018 Journal Article Quantitative susceptibility mapping for following intracranial hemorrhageSun, Hongfu, Klahr, Ana C., Kate, Mahesh, Gioia, Laura C., Emery, Derek J., Butcher, Kenneth S. and Wilman, Alan H. (2018). Quantitative susceptibility mapping for following intracranial hemorrhage. Radiology, 288 (3), 830-839. doi: 10.1148/radiol.2018171918 |
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Featured 2017 Journal Article Structural and functional quantitative susceptibility mapping from standard fMRI studiesSun, H., Seres, P. and Wilman, A. H. (2017). Structural and functional quantitative susceptibility mapping from standard fMRI studies. NMR in Biomedicine, 30 (4) e3619, e3619. doi: 10.1002/nbm.3619 |
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Featured 2016 Journal Article Quantitative susceptibility mapping using a superposed dipole inversion method: Application to intracranial hemorrhageSun, Hongfu, Kate, Mahesh, Gioia, Laura C., Emery, Derek J., Butcher, Kenneth and Wilman, Alan H. (2016). Quantitative susceptibility mapping using a superposed dipole inversion method: Application to intracranial hemorrhage. Magnetic Resonance in Medicine, 76 (3), 781-791. doi: 10.1002/mrm.25919 |
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2015 Journal Article Quantitative susceptibility mapping using single-shot echo-planar imagingSun, Hongfu and Wilman, Alan H. (2015). Quantitative susceptibility mapping using single-shot echo-planar imaging. Magnetic Resonance in Medicine, 73 (5), 1932-1938. doi: 10.1002/mrm.25316 |
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Featured 2015 Journal Article Validation of quantitative susceptibility mapping with Perls' iron staining for subcortical gray matterSun, Hongfu, Walsh, Andrew J., Lebel, R. Marc, Blevins, Gregg, Catz, Ingrid, Lu, Jian-Qiang, Johnson, Edward S., Emery, Derek J., Warren, Kenneth G. and Wilman, Alan H. (2015). Validation of quantitative susceptibility mapping with Perls' iron staining for subcortical gray matter. NeuroImage, 105, 486-492. doi: 10.1016/j.neuroimage.2014.11.010 |
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2014 Journal Article Background field removal using spherical mean value filtering and Tikhonov regularizationSun, Hongfu and Wilman, Alan H. (2014). Background field removal using spherical mean value filtering and Tikhonov regularization. Magnetic Resonance in Medicine, 71 (3), 1151-1157. doi: 10.1002/mrm.24765 |
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2025 Journal Article Quantitative susceptibility mapping via deep neural networks with iterative reverse concatenations and recurrent modulesLi, Min, Chen, Chen, Xiong, Zhuang, Liu, Yin, Rong, Pengfei, Shan, Shanshan, Liu, Feng, Sun, Hongfu and Gao, Yang (2025). Quantitative susceptibility mapping via deep neural networks with iterative reverse concatenations and recurrent modules. Medical Physics. doi: 10.1002/mp.17747 |
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2025 Journal Article MRF-mixer: a simulation-based deep learning framework for accelerated and accurate magnetic resonance fingerprinting reconstructionDing, Tianyi, Gao, Yang, Xiong, Zhuang, Liu, Feng, Cloos, Martijn A. and Sun, Hongfu (2025). MRF-mixer: a simulation-based deep learning framework for accelerated and accurate magnetic resonance fingerprinting reconstruction. Information, 16 (3) 218, 218. doi: 10.3390/info16030218 |
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2025 Journal Article Neoadjuvant SHR-1701 (a bifunctional anti-PD-L1/TGF-βRII agent) combined with chemoradiotherapy for resectable locally advanced esophageal squamous cell carcinoma (ESCC): A phase II trialLiu, Chengixn, Huang, Wei, Fu, Chengrui, Sun, Hongfu, Zhao, Qian, Zhao, Changhong, Chen, Xiaoyu and Li, Baosheng (2025). Neoadjuvant SHR-1701 (a bifunctional anti-PD-L1/TGF-βRII agent) combined with chemoradiotherapy for resectable locally advanced esophageal squamous cell carcinoma (ESCC): A phase II trial. Journal of Clinical Oncology, 43 (4_suppl), 410-410. doi: 10.1200/jco.2025.43.4_suppl.410 |
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2024 Conference Publication Fast controllable diffusion models for undersampled MRI reconstructionJiang, Wei, Xiong, Zhuang, Liu, Feng, Ye, Nan and Sun, Hongfu (2024). Fast controllable diffusion models for undersampled MRI reconstruction. 2024 IEEE International Symposium on Biomedical Imaging (ISBI), Athens, Greece, 27-30 May 2024. Piscataway, NJ, United States: IEEE. doi: 10.1109/isbi56570.2024.10635891 |
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2024 Journal Article Quantitative susceptibility mapping through model-based deep image prior (MoDIP)Xiong, Zhuang, Gao, Yang, Liu, Yin, Fazlollahi, Amir, Nestor, Peter, Liu, Feng and Sun, Hongfu (2024). Quantitative susceptibility mapping through model-based deep image prior (MoDIP). NeuroImage, 291 120583, 120583. doi: 10.1016/j.neuroimage.2024.120583 |
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2024 Journal Article Plug-and-Play latent feature editing for orientation-adaptive quantitative susceptibility mapping neural networksGao, Yang, Xiong, Zhuang, Shan, Shanshan, Liu, Yin, Rong, Pengfei, Li, Min, Wilman, Alan H., Pike, G. Bruce, Liu, Feng and Sun, Hongfu (2024). Plug-and-Play latent feature editing for orientation-adaptive quantitative susceptibility mapping neural networks. Medical Image Analysis, 94 103160, 1-11. doi: 10.1016/j.media.2024.103160 |
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2024 Conference Publication QSM Reconstruction of Arbitrary Dipole Orientations using an End-to-end Neural Network via Latent Feature EditingGao, Yang, Xiong, Zhuang, Shan, Shanshan, Li, Min, Wilman, Alan H, Pike, G. Bruce, Liu, Feng and Sun, Hongfu (2024). QSM Reconstruction of Arbitrary Dipole Orientations using an End-to-end Neural Network via Latent Feature Editing. 2024 ISMRM & ISMRT Annual Meeting, Singapore, 4-9 May 2024. Concord, CA United States: ISMRM. doi: 10.58530/2024/2453 |
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2023 Journal Article Editorial: Imaging of neurometabolismZheng, Wenbin, Dai, Zhouzhi, Wu, Renhua and Sun, Hongfu (2023). Editorial: Imaging of neurometabolism. Frontiers in Neuroscience, 17 1286361, 1286361. doi: 10.3389/fnins.2023.1286361 |
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2023 Journal Article MapFlow: latent transition via normalizing flow for unsupervised domain adaptationAskari, Hossein, Latif, Yasir and Sun, Hongfu (2023). MapFlow: latent transition via normalizing flow for unsupervised domain adaptation. Machine Learning, 112 (8), 2953-2974. doi: 10.1007/s10994-023-06357-2 |
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2023 Journal Article Increased glymphatic system activity in patients with mild traumatic brain injuryDai, Zhuozhi, Yang, Zhiqi, Li, Zhaolin, Li, Mu, Sun, Hongfu, Zhuang, Zerui, Yang, Weichao, Hu, Zehuan, Chen, Xiaofeng, Lin, Daiying and Wu, Xianheng (2023). Increased glymphatic system activity in patients with mild traumatic brain injury. Frontiers in Neurology, 14 1148878, 1-7. doi: 10.3389/fneur.2023.1148878 |
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2023 Journal Article Distortion‐corrected image reconstruction with deep learning on an MRI‐LinacShan, Shanshan, Gao, Yang, Liu, Paul Z. Y., Whelan, Brendan, Sun, Hongfu, Dong, Bin, Liu, Feng and Waddington, David E. J. (2023). Distortion‐corrected image reconstruction with deep learning on an MRI‐Linac. Magnetic Resonance in Medicine, 90 (3), 1-15. doi: 10.1002/mrm.29684 |
