Dr Hongfu Sun
Honorary Senior Research Fellow
School of Electrical Engineering & Computer Science
Researcher biography
Dr Hongfu Sun completed his PhD in Biomedical Engineering at the University of Alberta in 2015, followed by postdoctoral training in Calgary until 2018. He joined the Imaging, Sensing and Biomedical Engineering team in the School of ITEE at UQ in 2019 and was awarded the ARC DECRA fellowship in 2021. His research interests include developing novel magnetic resonance imaging (MRI) contrast mechanisms, e.g. Quantitative Susceptibility Mapping (QSM), fast and multi-parametric MRI acquisitions, and advanced image reconstruction techniques, including deep learning and artificial intelligence, to advance medical imaging techniques for clinical applications.
Dr Sun is currently recruiting graduate students. Check out Available Projects for details. Open to both Domestic and International students.
Journal Articles
Sun, Hongfu, Li, Minghao, Huang, Wei, Zhang, Jian, Wei, Shihong, Yang, Yongjing, Wang, Zhongtang, Ye, Shucheng, Gong, Heyi, Zhang, Yaowen, Li, Jie, Song, Haixia, Wang, Lifang, Chen, Xiangming, Lin, Haiqun, Ding, Gaofeng, Li, Hongwei, Zheng, Anping, Ma, Xuezhen, Chen, ShaoShui, Liu, Liping, Zhang, Kaixian, Fu, Chengrui, Liu, Wenzhi, Wang, Jing, Zhang, Xiaqin, Liu, Tingting, Han, Dan, Zhao, Qian ... Li, Baosheng (2024). Thoracic Radiotherapy Improves the Survival in Patients With
EGFR
-Mutated Oligo-Organ Metastatic Non–Small Cell Lung Cancer Treated With Epidermal Growth Factor Receptor–Tyrosine Kinase Inhibitors: A Multicenter, Randomized, Controlled, Phase III Trial. Journal of Clinical Oncology. doi: 10.1200/jco.23.02075
Li, Bobo, Guo, Xiaokang, Yu, Jiaqi, Sun, Hongfu, Zhao, Xiaoming, Sun, Yan, Dai, Xianling, Kuang, Qin, Ling, Jimao and Liu, Jie (2024). Targeting cancer stress-associated hyperinsulinemia and abnormal behavior mitigates lung carcinoma in postmenopausal mouse: Intervention function of peimine. Journal of Functional Foods, 121 106400, 106400. doi: 10.1016/j.jff.2024.106400
Gao, Xinyu, Liu, Tingting, Fan, Min, Sun, Hongfu, Zhou, Shixuan, Zhou, Yuxin, Zhu, Haolin, Zhang, Ru, Li, Zhanyuan and Huang, Wei (2024). Correction: The therapeutic effect of radiotherapy combined with systemic therapy compared to radiotherapy alone in patients with simple brain metastasis after first-line treatment of limited-stage small cell lung cancer: a retrospective study. World Journal of Surgical Oncology, 22 (1) 252. doi: 10.1186/s12957-024-03531-1
Han, Dan, Dong, Jinling, Wang, Qifeng, Li, Baosheng, Liu, Jun, Liu, Hui, Qiu, Bo, Zhang, Wencheng, Yang, Hong, Shen, Wenbin, Zhang, Yaowen, Zhu, Xiangzhi, Wang, Yi, Wu, Lei, Sun, Hongfu and Huang, Wei (2024). Neoadjuvant radiation target volume definition in esophageal squamous cell cancer: a multicenter recommendations from Chinese experts. BMC Cancer, 24 (1) 1086. doi: 10.1186/s12885-024-12825-2
Yang, Lei, Tang, Yuegang, Sun, Hongfu, He, Lingling and Li, Ruiqing (2024). Hydrochemical characteristics of abandoned coal mines derived acid mine drainage in a typical karst basin (Wuma river basin, Guizhou China). Heliyon, 10 (11) ARTN e31963, e31963. doi: 10.1016/j.heliyon.2024.e31963
Gao, 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, 103160. doi: 10.1016/j.media.2024.103160
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
Ren, Yu, Wang, Guoli, Wang, Pingping, Liu, Kunmeng, Liu, Quanjin, Sun, Hongfu, Li, Xiang and Wei, Bengzheng (2024). MM-SFENet: multi-scale multi-task localization and classification of bladder cancer in MRI with spatial feature encoder network. Physics in Medicine and Biology, 69 (2) ARTN 025009. doi: 10.1088/1361-6560/ad1548
Zhang, Meng, Lu, Yukun, Sun, Hongfu, Hou, Chuanke, Zhou, Zichun, Liu, Xiao, Zhou, Qichao, Li, Zhenjiang and Yin, Yong (2023). CT-based deep learning radiomics and hematological biomarkers in the assessment of pathological complete response to neoadjuvant chemoradiotherapy in patients with esophageal squamous cell carcinoma: A two-center study. Translational Oncology, 39 ARTN 101804, 101804. doi: 10.1016/j.tranon.2023.101804
Zheng, 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
Askari, 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
Dai, 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
Shan, 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
Xiong, Zhuang, Gao, Yang, Liu, Feng and Sun, Hongfu (2023). Affine transformation edited and refined deep neural network for quantitative susceptibility mapping. NeuroImage, 267 119842, 1-9. doi: 10.1016/j.neuroimage.2022.119842
Nathoo, Nabeela, Gee, Myrlene, Nelles, Krista, Burt, Jacqueline, Sun, Hongfu, Seres, Peter, Wilman, Alan H., Beaulieu, Christian, Ba, Fang and Camicioli, Richard (2022). Quantitative susceptibility mapping changes relate to gait issues in Parkinson’s Disease. Canadian Journal of Neurological Sciences, 50 (6) PII S031716712200316X, 1-8. doi: 10.1017/cjn.2022.316
Yang, Runze, Hamilton, A. Max, Sun, Hongfu, Rawji, Khalil S., Sarkar, Susobhan, Mirzaei, Reza, Pike, G. Bruce, Yong, V. Wee. and Dunn, Jeff F. (2022). Detecting monocyte trafficking in an animal model of glioblastoma using R2* and quantitative susceptibility mapping. Cancer Immunology, Immunotherapy, 72 (3), 733-742. doi: 10.1007/s00262-022-03297-z
De, Ashmita, Sun, Hongfu, Emery, Derek J., Butcher, Kenneth S. and Wilman, Alan H. (2022). Quantitative susceptibility-weighted imaging in presence of strong susceptibility sources: application to hemorrhage. Magnetic Resonance Imaging, 92, 224-231. doi: 10.1016/j.mri.2022.06.010
Nakhid, Daphne, McMorris, Carly, Sun, Hongfu, Gibbard, William Benton, Tortorelli, Christina and Lebel, Catherine (2022). Brain volume and magnetic susceptibility differences in children and adolescents with prenatal alcohol exposure. Alcoholism: Clinical and Experimental Research, 46 (10), 1797-1807. doi: 10.1111/acer.14928
Gao, Yang, Xiong, Zhuang, Fazlollahi, Amir, Nestor, Peter J., Vegh, Viktor, Nasrallah, Fatima, Winter, Craig, Pike, G. Bruce, Crozier, Stuart, Liu, Feng and Sun, Hongfu (2022). Instant tissue field and magnetic susceptibility mapping from MRI raw phase using Laplacian enhanced deep neural networks. NeuroImage, 259 119410, 1-13. doi: 10.1016/j.neuroimage.2022.119410
Zhu, Xuanyu, Gao, Yang, Liu, Feng, Crozier, Stuart and Sun, Hongfu (2022). BFRnet: A deep learning-based MR background field removal method for QSM of the brain containing significant pathological susceptibility sources. Zeitschrift fur Medizinische Physik, 33 (4), 578-590. doi: 10.1016/j.zemedi.2022.08.001
Nakhid, Daphne, McMorris, Carly A., Sun, Hongfu, Gibbard, Ben, Tortorelli, Christina and Lebel, Catherine (2022). Brain iron and mental health symptoms in youth with and without prenatal alcohol exposure. Nutrients, 14 (11) 2213, 1-18. doi: 10.3390/nu14112213
Yang, Zhiqi, Lin, Daiying, Chen, Xiaofeng, Qiu, Jinming, Li, Shengkai, Huang, Ruibin, Yang, Zhijian, Sun, Hongfu, Liao, Yuting, Xiao, Jianning, Tang, Yanyan, Chen, Xiangguang, Zhang, Sheng and Dai, Zhuozhi (2022). Distinguishing COVID-19 from influenza pneumonia in the early stage through CT imaging and clinical features. Frontiers in Microbiology, 13 847836, 1-9. doi: 10.3389/fmicb.2022.847836
Zhu, Xuanyu, Gao, Yang, Liu, Feng, Crozier, Stuart and Sun, Hongfu (2022). Deep grey matter quantitative susceptibility mapping from small spatial coverages using deep learning. Zeitschrift fur Medizinische Physik, 32 (2), 188-198. doi: 10.1016/j.zemedi.2021.06.004
Gao, Yang, Cloos, Martijn, Liu, Feng, Crozier, Stuart, Pike, G. Bruce and Sun, Hongfu (2021). Accelerating quantitative susceptibility and R2* mapping using incoherent undersampling and deep neural network reconstruction. NeuroImage, 240 118404, 1-13. doi: 10.1016/j.neuroimage.2021.118404
Zhao, Dexin, Zhu, Lin, Sun, Hongfu, Li, Jun and Wang, Weishi (2021). Fengyun-3D/MERSI-II cloud thermodynamic phase determination using a machine-learning approach. Remote Sensing, 13 (12) 2251, 1-18. doi: 10.3390/rs13122251
Liu, Xinwen, Wang, Jing, Sun, Hongfu, Chandra, Shekhar S, Crozier, Stuart and Liu, Feng (2021). On the regularization of feature fusion and mapping for fast MR multi-contrast imaging via iterative networks. Magnetic resonance imaging, 77, 159-168. doi: 10.1016/j.mri.2020.12.019
Gao, Yang, Zhu, Xuanyu, Moffat, Bradford A., Glarin, Rebecca, Wilman, Alan H., Pike, G. Bruce, Crozier, Stuart, Liu, Feng and Sun, Hongfu (2021). xQSM: quantitative susceptibility mapping with octave convolutional and noise-regularized neural networks. NMR in Biomedicine, 34 (3) e4461, e4461. doi: 10.1002/nbm.4461
Yang, Zhiqi, Chen, Xiaofeng, Huang, Ruibin, Li, Shengkai, Lin, Daiying, Yang, Zhijian, Sun, Hongfu, Liu, Guorui, Qiu, Jinming, Tang, Yanyan, Xiao, Jianning, Liao, Yuting, Wu, Xianheng, Wu, Renhua, Chen, Xiangguang and Dai, Zhuozhi (2021). Atypical presentations of coronavirus disease 2019 (COVID-19) from onset to readmission. BMC Infectious Diseases, 21 (1) 127, 127. doi: 10.1186/s12879-020-05751-8
MacDonald, M. Ethan, Williams, Rebecca J., Rajashekar, Deepthi, Stafford, Randall B., Hanganu, Alexadru, Sun, Hongfu, Berman, Avery J.L., McCreary, Cheryl R., Frayne, Richard, Forkert, Nils D. and Pike, G. Bruce (2020). Age-related differences in cerebral blood flow and cortical thickness with an application to age prediction. Neurobiology of Aging, 95, 131-142. doi: 10.1016/j.neurobiolaging.2020.06.019
Dai, Zhuozhi, Kalra, Sanjay, Mah, Dennell, Seres, Peter, Sun, Hongfu, Wu, Renhua and Wilman, Alan H. (2020). Amide signal intensities may be reduced in the motor cortex and the corticospinal tract of ALS patients. European Radiology, 31 (3), 1401-1409. doi: 10.1007/s00330-020-07243-4
Ma, Yuhan, Mazerolle, Erin L., Cho, Junghun, Sun, Hongfu, Wang, Yi and Pike, G. Bruce (2020). Quantification of brain oxygen extraction fraction using QSM and a hyperoxic challenge. Magnetic Resonance in Medicine, 84 (6) mrm.28390, 3271-3285. doi: 10.1002/mrm.28390
Chen, Xiaofeng, Tang, Yanyan, Mo, Yongkang, Li, Shengkai, Lin, Daiying, Yang, Zhijian, Yang, Zhiqi, Sun, Hongfu, Qiu, Jinming, Liao, Yuting, Xiao, Jianning, Chen, Xiangguang, Wu, Xianheng, Wu, Renhua and Dai, Zhuozhi (2020). A diagnostic model for coronavirus disease 2019 (COVID-19) based on radiological semantic and clinical features: a multi-center study. European Radiology, 30 (9), 4893-4902. doi: 10.1007/s00330-020-06829-2
Zhao, Qian, Liu, Ming, Wang, Zhongtang, Huang, Wei, Li, X. Allen, Zhou, Tao, Zhang, Jian, Zhang, Zicheng, Wang, Qiang, Yu, Shuzeng, Han, Dan, Sun, Hongfu, Li, Hongsheng, Lin, Haiqun and Li, Baosheng (2020). High dose radiation therapy based on normal tissue constraints with concurrent chemotherapy achieves promising survival of patients with unresectable stage III non-small cell lung cancer. Radiotherapy and Oncology, 145, 7-12. doi: 10.1016/j.radonc.2019.11.024
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
Naji, Nashwan, Sun, Hongfu and Wilman, Alan H. (2020). On the value of QSM from MPRAGE for segmenting and quantifying iron-rich deep gray matter. Magnetic Resonance in Medicine, 84 (3) mrm.28226, 1486-1500. doi: 10.1002/mrm.28226
Zhu, Weiren, Zhu, Lin, Li, Jun and Sun, Hongfu (2020). Retrieving Volcanic Ash Top Height through Combined Polar Orbit Active and Geostationary Passive Remote Sensing Data. Remote Sensing, 12 (6) 953, 1-21. doi: 10.3390/rs12060953
Sun, 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
Ma, Yuhan, Sun, Hongfu, Cho, Junghun, Mazerolle, Erin L., Wang, Yi and Pike, G. Bruce (2019). Cerebral OEF quantification: a comparison study between quantitative susceptibility mapping and dual‐gas calibrated BOLD imaging. Magnetic Resonance in Medicine, 83 (1) mrm.27907, 68-82. doi: 10.1002/mrm.27907
Elkady, Ahmed M., Cobzas, Dana, Sun, Hongfu, Seres, Peter, Blevins, Gregg and Wilman, Alan H. (2019). Five year iron changes in relapsing-remitting multiple sclerosis deep gray matter compared to healthy controls. Multiple Sclerosis and Related Disorders, 33, 107-115. doi: 10.1016/j.msard.2019.05.028
De, Ashmita, Sun, Hongfu, Emery, Derek J., Butcher, Kenneth S. and Wilman, Alan H. (2019). Rapid quantitative susceptibility mapping of intracerebral hemorrhage. Journal of Magnetic Resonance Imaging, 51 (3) jmri.26850, 712-718. doi: 10.1002/jmri.26850
Sun, 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
Sun, 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
Elkady, Ahmed M., Cobzas, Dana, Sun, Hongfu, Blevins, Gregg and Wilman, Alan H. (2018). Discriminative analysis of regional evolution of iron and myelin/calcium in deep gray matter of multiple sclerosis and healthy subjects. Journal of Magnetic Resonance Imaging, 48 (3), 652-668. doi: 10.1002/jmri.26004
Walsh, A. J., Sun, H., Emery, D. J. and Wilman, A. H. (2018). Hematocrit measurement with R2* and quantitative susceptibility mapping in postmortem brain. American Journal of Neuroradiology, 39 (7), 1260-1266. doi: 10.3174/ajnr.A5677
Elkady, Ahmed M., Cobzas, Dana, Sun, Hongfu, Blevins, Gregg and Wilman, Alan H. (2017). Progressive iron accumulation across multiple sclerosis phenotypes revealed by sparse classification of deep gray matter. Journal of Magnetic Resonance Imaging, 46 (5), 1464-1473. doi: 10.1002/jmri.25682
Fujiwara, E., Kmech, J. A., Cobzas, D., Sun, H., Seres, P., Blevins, G. and Wilman, A. H. (2017). Cognitive implications of deep gray matter iron in multiple sclerosis. American Journal of Neuroradiology, 38 (5), 942-948. doi: 10.3174/ajnr.A5109
Juhas, Michal, Sun, Hongfu, Brown, Matthew R. G., MacKay, Marnie B., Mann, Karl F., Sommer, Wolfgang H., Wilman, Alan H., Dursun, Serdar M. and Greenshaw, Andrew J. (2017). Deep grey matter iron accumulation in alcohol use disorder. NeuroImage, 148, 115-122. doi: 10.1016/j.neuroimage.2017.01.007
Sun, 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
Sun, 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
Elkady, Ahmed M., Sun, Hongfu and Wilman, Alan H. (2016). Importance of extended spatial coverage for quantitative susceptibility mapping of iron-rich deep gray matter. Magnetic Resonance Imaging, 34 (4), 574-578. doi: 10.1016/j.mri.2015.12.032
Cobzas, Dana, Sun, Hongfu, Walsh, Andrew J., Lebel, R. Marc, Blevins, Gregg and Wilman, Alan H. (2015). Subcortical gray matter segmentation and voxel-based analysis using transverse relaxation and quantitative susceptibility mapping with application to multiple sclerosis. Journal of Magnetic Resonance Imaging, 42 (6), 1601-1610. doi: 10.1002/jmri.24951
Sun, 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
Sun, 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
Sun, 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
Conference Papers
Jiang, 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
Gao, Yang, Xiong, Zhuang, Fazlollahi, Amir, Nestor, Peter, Vegh, Viktor, Pike, G. Bruce, Crozier, Stuart, Liu, Feng and Sun, Hongfu (2023). QSM from the raw phase using an end-to-end neural network. ISMRM Annual Meeting, London, United Kingdom, 7-12 May 2022. Berkeley, CA, United States: International Society for Magnetic Resonance in Medicine. doi: 10.58530/2022/4740
Gao, Yang, Liu, Feng, Crozier, Stuart and Sun, Hongfu (2021). Accelerating QSM using compressed sensing and deep neural network. 2021 ISMRM & SMRT Annual Meeting & Exhibition, Online, 15-20 May 2021. Berkeley, CA, United States: International Society for Magnetic Resonance in Medicine.
Liu, Xinwen, Wang, Jing, Tang, Fangfang, Sun, Hongfu, Liu, Feng and Crozier, Stuart (2020). Rapid region-of-interest MRI reconstruction using context-aware rapid region-of-interest MRI reconstruction using context-aware non-local U-net. ISMRM & SMRT Virtual Conference & Exhibition, 2020, Virtual, 8-14 August 2020.
Sun, Hongfu, MacDonald, M. Ethan, Lebel, R. Marc and Pike, G. Bruce (2020). Simultaneous T1-weighted imaging, R2* mapping, and QSM from a multi-echo MPRAGE sequence using a radial fan-beam sampling scheme at 3 Tesla. ISMRM & SMRT Virtual Conference & Exhibition, Online, 8-14 August 2020. Berkeley, CA, United States: International Society for Magnetic Resonance in Medicine.