Professor Feng Liu
Professor

Feng Liu

Email: 
Phone: 
+61 7 336 53982

Availability

Professor Feng Liu is:
Available for supervision
Media expert

Fields of research

Biomedical engineering

Qualifications

  • Bachelor of Engineering, Shandong University (山东大学)
  • Masters (Coursework) of Science, Shandong University (山东大学)
  • Doctor of Philosophy, Zhejiang University

Research interests

  • Research interests

    My research lies in medical imaging, with the focus on magnetic resonance imaging (MRI) hardware design and electromagnetic analysis + cardiac electrical function imaging. My current research program includes: (1) Magnetic Resonance Engineering (Electromagnetic Analysis and Design); (2) Magnetic Resonance Imaging (MRI Image reconstruction, including parallel imaging, compressed sensing, etc.); (3) Bioelectromagnetism (AI-based ECG; TMS designs); (4) Computational Electromagnetics (in particular, Finite-difference Time-domain (FDTD)); (5) Engineering Optimization; (6) High-performance Parallel Computing (in particular, GPU computing). (7) Machine learning/deep learning based medical imaging. I am currently recruiting graduate students. Check out Available Projects for details. Open to both Domestic and International students currently onshore.

Search Professor Feng Liu’s works on UQ eSpace

575 works between 1997 and 2026
All (575) Journal Article (392) Other Outputs (3) Conference Publication (180)

201 - 220 of 575 works

2020

Journal Article

Nanozyme-mediated cascade reaction based on metal-organic framework for synergetic chemo-photodynamic tumor therapy

Sheng, Shu, Liu, Feng, Lin, Lin, Yan, Nan, Wang, Yanbing, Xu, Caina, Tian, Huayu and Chen, Xuesi (2020). Nanozyme-mediated cascade reaction based on metal-organic framework for synergetic chemo-photodynamic tumor therapy. Journal of Controlled Release, 328, 631-639. doi: 10.1016/j.jconrel.2020.09.029

Nanozyme-mediated cascade reaction based on metal-organic framework for synergetic chemo-photodynamic tumor therapy

2020

Journal Article

A dedicated eight‐channel receive RF coil array for monkey brain MRI at 9.4 T

Li, Mingyan, Li, Yu, Jin, Jin, Yang, Zhengyi, Zhang, Baogui, Liu, Yanyan, Song, Ming, Freakly, Craig, Weber, Ewald, Liu, Feng, Jiang, Tianzi and Crozier, Stuart (2020). A dedicated eight‐channel receive RF coil array for monkey brain MRI at 9.4 T. NMR in Biomedicine, 33 (10) e4369, 1-16. doi: 10.1002/nbm.4369

A dedicated eight‐channel receive RF coil array for monkey brain MRI at 9.4 T

2020

Journal Article

Fast geometric distortion correction using a deep neural network: implementation for the 1 Tesla MRI-Linac system

Li, Mao, Shan, Shanshan, Chandra, Shekhar S., Liu, Feng and Crozier, Stuart (2020). Fast geometric distortion correction using a deep neural network: implementation for the 1 Tesla MRI-Linac system. Medical Physics, 47 (9) mp.14382, 4303-4315. doi: 10.1002/mp.14382

Fast geometric distortion correction using a deep neural network: implementation for the 1 Tesla MRI-Linac system

2020

Conference Publication

Rapid region-of-interest MRI reconstruction using context-aware rapid region-of-interest MRI reconstruction using context-aware non-local U-net

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.

Rapid region-of-interest MRI reconstruction using context-aware rapid region-of-interest MRI reconstruction using context-aware non-local U-net

2020

Conference Publication

Deep simultaneous optimization of sampling and reconstruction for multi-contrast MRI

Liu, Xinwen, Wang, Jing, Tang, Fangfang, Chandra, Shekhar S., Liu, Feng and Crozier, Stuart (2020). Deep simultaneous optimization of sampling and reconstruction for multi-contrast MRI. ISMRM & SMRT Virtual Conference & Exhibition, 2020, Online, 8-14 August 2020.

Deep simultaneous optimization of sampling and reconstruction for multi-contrast MRI

2020

Journal Article

Catalytic decarboxylative radical sulfonylation

He, Jiayan, Chen, Guangle, Zhang, Benxiang, Li, Yi, Chen, Jia-Rong, Xiao, Wen-Jing, Liu, Feng and Li, Chaozhong (2020). Catalytic decarboxylative radical sulfonylation. Chem, 6 (5), 1149-1159. doi: 10.1016/j.chempr.2020.02.003

Catalytic decarboxylative radical sulfonylation

2020

Journal Article

Ancient DNA indicates human population shifts and admixture in northern and southern China

Yang, Melinda A., Fan, Xuechun, Sun, Bo, Chen, Chungyu, Lang, Jianfeng, Ko, Ying-Chin, Tsang, Cheng-Hwa, Chiu, Hunglin, Wang, Tianyi, Bao, Qingchuan, Wu, Xiaohong, Hajdinjak, Mateja, Ko, Albert Min-Shan, Ding, Manyu, Cao, Peng, Yang, Ruowei, Liu, Feng, Nickel, Birgit, Dai, Qingyan, Feng, Xiaotian, Zhang, Lizhao, Sun, Chengkai, Ning, Chao, Zeng, Wen, Zhao, Yongsheng, Zhang, Ming, Gao, Xing, Cui, Yinqiu, Reich, David ... Fu, Qiaomei (2020). Ancient DNA indicates human population shifts and admixture in northern and southern China. Science, 369 (6501), 282-288. doi: 10.1126/science.aba0909

Ancient DNA indicates human population shifts and admixture in northern and southern China

2020

Journal Article

Magnetic resonance-electrical properties tomography by directly solving Maxwell’s Curl Equations

Chi, Jieru, Guo, Lei, Destruel, Aurelien, Wang, Yaohui, Liu, Chunyi, Li, Mingyan, Weber, Ewald, Liu, Qinghuo, Yang, Jie, Xin, Xuegang and Liu, Feng (2020). Magnetic resonance-electrical properties tomography by directly solving Maxwell’s Curl Equations. Applied Sciences, 10 (9) 3318, 1-13. doi: 10.3390/app10093318

Magnetic resonance-electrical properties tomography by directly solving Maxwell’s Curl Equations

2020

Journal Article

Ancient DNA evidence from China reveals the expansion of Pacific dogs

Zhang, Ming, Sun, Guoping, Ren, Lele, Yuan, Haibing, Dong, Guanghui, Zhang, Lizhao, Liu, Feng, Cao, Peng, Ko, Albert Min-Shan, Yang, Melinda A., Hu, Songmei, Wang, Guo-Dong and Fu, Qiaomei (2020). Ancient DNA evidence from China reveals the expansion of Pacific dogs. Molecular Biology and Evolution, 37 (5), 1462-1469. doi: 10.1093/molbev/msz311

Ancient DNA evidence from China reveals the expansion of Pacific dogs

2020

Journal Article

Insert magnet and shim coils design for a 27 T NMR spectrometer with hybrid high and low temperature superconductors

Wang, Yaohui, Wang, Qiuliang, Liu, Jianhua, Cheng, Junsheng and Liu, Feng (2020). Insert magnet and shim coils design for a 27 T NMR spectrometer with hybrid high and low temperature superconductors. Superconductor Science and Technology, 33 (6) 064004, 064004. doi: 10.1088/1361-6668/ab861a

Insert magnet and shim coils design for a 27 T NMR spectrometer with hybrid high and low temperature superconductors

2020

Journal Article

Sentiment Recognition for Short Annotated GIFs Using Visual-Textual Fusion

Liu, Tianliang, Wan, Junwei, Dai, Xiubin, Liu, Feng, You, Quanzeng and Luo, Jiebo (2020). Sentiment Recognition for Short Annotated GIFs Using Visual-Textual Fusion. Ieee Transactions On Multimedia, 22 (4), 1098-1110. doi: 10.1109/TMM.2019.2936805

Sentiment Recognition for Short Annotated GIFs Using Visual-Textual Fusion

2020

Journal Article

Electromagnetic design of a 1.5T open MRI superconducting magnet

Wang, Yaohui, Wang, Qiuliang, Wang, Lei, Qu, Hongyi, Liu, Yang and Liu, Feng (2020). Electromagnetic design of a 1.5T open MRI superconducting magnet. Physica C: Superconductivity and its Applications, 570 1353602, 1-8. doi: 10.1016/j.physc.2020.1353602

Electromagnetic design of a 1.5T open MRI superconducting magnet

2020

Journal Article

Partial wave analysis of ψ(3686) → K<sup>+</sup> K<sup>-</sup> η

Ablikim, M., Achasov, M. N., Adlarson, P., Ahmed, S., Albrecht, M., Alekseev, M., Amoroso, A., An, F. F., An, Q., Bai, Y., Bakina, O., Ferroli, R. Baldini, Balossino,, Ban, Y., Begzsuren, K., Bennett, J., Berger, N., Bertani, M., Bettoni, D., Bianchi, F., Biernat, J., Bloms, J., Boyko,, Briere, R. A., Cai, H., Cai, X., Calcaterra, A., Cao, G. F., Cao, N. ... Zou, J. H. (2020). Partial wave analysis of ψ(3686) → K+ K- η. Physical Review D, 101 (3) 032008, 1-12. doi: 10.1103/PhysRevD.101.032008

Partial wave analysis of ψ(3686) → K<sup>+</sup> K<sup>-</sup> η

2020

Journal Article

Statistical analysis of the accuracy of water content‐based electrical properties tomography

Han, Jijun, Gao, Yunyu, Nan, Xiang, Liu, Feng and Xin, Sherman Xuegang (2020). Statistical analysis of the accuracy of water content‐based electrical properties tomography. NMR in Biomedicine, 33 (5) e4273, e4273. doi: 10.1002/nbm.4273

Statistical analysis of the accuracy of water content‐based electrical properties tomography

2020

Journal Article

Association of apolipoprotein E polymorphisms with white matter lesions and brain atrophy

Niu, ZhiLi, Zhang, PingAn, Li, Dong, Zhu, ChengLiang, Feng, LiNa, Xiong, Ge, Song, NaNa, Tang, Pei and Liu, Feng (2020). Association of apolipoprotein E polymorphisms with white matter lesions and brain atrophy. Psychiatry Investigation, 17 (2), 96-105. doi: 10.30773/pi.2019.0090

Association of apolipoprotein E polymorphisms with white matter lesions and brain atrophy

2020

Journal Article

Integrating model- and data-driven methods for synchronous adaptive multi-band image fusion

Lin, Suzhen, Han, Ze, Li, Dawei, Zeng, Jianchao, Yang, Xiaoli, Liu, Xinwen and Liu, Feng (2020). Integrating model- and data-driven methods for synchronous adaptive multi-band image fusion. Information Fusion, 54, 145-160. doi: 10.1016/j.inffus.2019.07.009

Integrating model- and data-driven methods for synchronous adaptive multi-band image fusion

2020

Journal Article

Cross section measurement of e<sup>+</sup> e<sup>-</sup> → η′ J/ψ from √S=4.178 to 4.600 GeV

Ablikim, M., Achasov, M. N., Adlarson, P., Ahmed, S., Albrecht, M., Alekseev, M., Amoroso, A., An, F. F., An, Q., Bai, Y., Bakina, O., Ferroli, R. Baldini, Balossino, I., Ban, Y., Begzsuren, K., Bennett, J. V., Berger, N., Bertani, M., Bettoni, D., Bianchi, F., Biernat, J., Bloms, J., Boyko, I., Briere, R. A., Cai, H., Cai, X., Calcaterra, A., Cao, G. F., Cao, N. ... Zou, J. H. (2020). Cross section measurement of e+ e- → η′ J/ψ from √S=4.178 to 4.600 GeV. Physical Review D, 101 (1) 012008, 1-9. doi: 10.1103/PhysRevD.101.012008

Cross section measurement of e<sup>+</sup> e<sup>-</sup> → η′ J/ψ from √S=4.178 to 4.600 GeV

2020

Journal Article

Geometric distortion characterization and correction for the 1.0 T Australian MRI-linac system using an inverse electromagnetic method

Shan, Shanshan, Liney, Gary P., Tang, Fangfang, Li, Mingyan, Wang, Yaohui, Ma, Huan, Weber, Ewald, Walker, Amy, Holloway, Lois, Wang, Qiuliang, Wang, Deming, Liu, Feng and Crozier, Stuart (2020). Geometric distortion characterization and correction for the 1.0 T Australian MRI-linac system using an inverse electromagnetic method. Medical Physics, 47 (3) mp.13979, 1126-1138. doi: 10.1002/mp.13979

Geometric distortion characterization and correction for the 1.0 T Australian MRI-linac system using an inverse electromagnetic method

2020

Journal Article

A Hybrid Intrusion Detection System for IoT Applications with Constrained Resources

Wu, Chao, Liu, Yuan'an, Wu, Fan, Liu, Feng, Lu, Hui, Fan, Wenhao and Tang, Bihua (2020). A Hybrid Intrusion Detection System for IoT Applications with Constrained Resources. International Journal of Digital Crime and Forensics, 12 (1), 109-130. doi: 10.4018/IJDCF.2020010106

A Hybrid Intrusion Detection System for IoT Applications with Constrained Resources

2020

Journal Article

Numerical experiments on the contrast capability of magnetic resonance electrical property tomography

Duan, Song, Zhu, Yurong, Liu, Feng and Xin, Sherman Xuegang (2020). Numerical experiments on the contrast capability of magnetic resonance electrical property tomography. Magnetic Resonance in Medical Sciences, 19 (1), 77-85. doi: 10.2463/mrms.mp.2018-0167

Numerical experiments on the contrast capability of magnetic resonance electrical property tomography

Current funding

  • 2024 - 2027
    Quantum-Enabled Low-Field Magnetic Resonance Imaging for High-Performance Sport
    Quantum 2032 Challenge Program
    Open grant
  • 2024 - 2026
    Disambiguating Parkinson's disease from disorders with mimicking symptoms using ultra-high-field (7 Tesla) multi-modal MRI
    NHMRC IDEAS Grants
    Open grant
  • 2023 - 2026
    Tissue Bio-physicochemical Quantification Using Magnetic Resonance Imaging
    ARC Discovery Projects
    Open grant

Past funding

  • 2023 - 2024
    Versatile Physical Property Measurement System for South-East Queensland (ARC LIEF administered by Queensland University of Technology)
    Queensland University of Technology
    Open grant
  • 2022 - 2025
    Evaluation of 7T 8-channel MRI coil for imaging of the human spine
    Aix-Marseille University
    Open grant
  • 2018 - 2022
    Dielectric contrast imaging for 7 Tesla Magnetic Resonance applications
    ARC Discovery Projects
    Open grant
  • 2016 - 2020
    Rotating Radiofrequency Phased-array for 7 Tesla Magnetic Resonance Imaging
    ARC Discovery Projects
    Open grant
  • 2014 - 2016
    Advanced Magnetic Resonance Imaging at 7 Tesla: Resolving the fundamental radiofrequency field-tissue interaction problem at ultra-high field
    ARC Discovery Projects
    Open grant
  • 2013 - 2016
    Heteronuclear parallel imaging and spectroscopy for Magnetic Resonance
    ARC Linkage Projects
    Open grant
  • 2013 - 2016
    Real-time cardiac magnetic resonance imaging: a compressed-sensing framework incorporating sensor design and multidimensional signal reconstruction
    ARC Discovery Projects
    Open grant
  • 2010 - 2012
    Solutions for reducing magnetic resonance image degradations and tissue heating at high frequencies
    ARC Discovery Projects
    Open grant
  • 2010
    UQ Travel Awards #2 - Feng LIU
    UQ Travel Grants Scheme
    Open grant
  • 2008 - 2011
    Transceive Phased Arrays for Parallel Imaging in High Field Magnetic Resonance Microscopy.
    ARC Linkage Projects
    Open grant
  • 2007 - 2011
    UQ Mid-Career Research Fellowship Start-Up Funding: Bioelectromagnetics and medical diagnostics
    UQ Mid-Career Research Fellowship
    Open grant
  • 2005 - 2007
    Cardiac electrographic modelling and analysis
    ARC Discovery Projects
    Open grant

Availability

Professor Feng Liu is:
Available for supervision

Looking for a supervisor? Read our advice on how to choose a supervisor.

Available projects

  • AI-based Magnetic Resonance Imaging

  • Novel Hardware design in MRI

  • AI-based ECG study

  • Computational Electromagnetics and Its Application in MRI

  • Novel Imaging Methods in MRI

Supervision history

Current supervision

  • Doctor Philosophy

    Radio-frequency system design for magnetic resonance imaging at 7 Tesla

    Principal Advisor

  • Doctor Philosophy

    Passive shimming and electromagnetic contrast imaging at ultrahigh field MRI

    Principal Advisor

  • Doctor Philosophy

    Diagnosis of Arrhythmia using ECG signal classification by neural networks

    Principal Advisor

  • Doctor Philosophy

    Deep Neural Architectures for Robust Feature Localization in Computer Tomography and Spectroscopy

    Principal Advisor

    Other advisors: Professor Kwun Fong, Associate Professor Henry Marshall, Dr Hongfu Sun

  • Doctor Philosophy

    Improving Artificial Intelligence And Deep Learning Algorithms In Super-Resolution Imaging

    Principal Advisor

  • Doctor Philosophy

    AI-empowered super-resolution MRI

    Principal Advisor

  • Doctor Philosophy

    A novel radio-frequency (RF) antenna system for X-nuclei magnetic resonance imaging

    Principal Advisor

  • Doctor Philosophy

    Deep learning based method for magnetic resonance fingerprinting reconstruction

    Associate Advisor

    Other advisors: Dr Hongfu Sun

  • Doctor Philosophy

    MR image processing through advanced optimisation techniques and deep learning

    Associate Advisor

    Other advisors: Dr Hongfu Sun

  • Doctor Philosophy

    MR image processing through advanced optimisation techniques and deep learning

    Associate Advisor

    Other advisors: Dr Hongfu Sun

  • Doctor Philosophy

    Development of novel deep learning methods for medical imaging

    Associate Advisor

    Other advisors: Dr Nan Ye, Dr Hongfu Sun

Completed supervision

Enquiries

Contact Professor Feng Liu directly for media enquiries about:

  • BioElectromagnetics
  • BioMechanical Engineering
  • Biomedical Engineering
  • Computational Electromagnetics
  • Engineering optimisation
  • Magnetic Resonance Imaging (MRI)

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