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

491 works between 1997 and 2025
All (491) Journal Article (318) Conference Publication (170) Other Outputs (3)

221 - 240 of 491 works

2016

Conference Publication

Development of high magnetic field magnet technologies for the magnetic resonance medical imaging

Wang, Qiu Liang, Yang, Wen Hui, Liu, Feng, Xia, Ling, Li, Yi, Ni, Zhi Peng, Yan, Lu Guang, Xu, Jian Yi, Cheng, Jun Sheng and Wang, Hui (2016). Development of high magnetic field magnet technologies for the magnetic resonance medical imaging. 2015 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices (ASEMD), Shanghai, China, 20-23 November 2015. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/ASEMD.2015.7453633

Development of high magnetic field magnet technologies for the magnetic resonance medical imaging

2016

Conference Publication

IBEM applied to the design of gradient coils for superconducting MRI

Hu, Yang, Hu, Xin Ning, Yan, Lu Guang, Liu, Feng and Fang, You Tong (2016). IBEM applied to the design of gradient coils for superconducting MRI. IEEE International Conference on Applied Superconductivity and Electromagnetic Devices, ASEMD 2015, Shanghai, China, 20-23 November 2015. Institute of Electrical and Electronics Engineers Inc.. doi: 10.1109/ASEMD.2015.7453636

IBEM applied to the design of gradient coils for superconducting MRI

2016

Journal Article

Intra-coil interactions in split gradient coils in a hybrid MRI-LINAC system

Tang, Fangfang, Freschi, Fabio, Sanchez Lopez, Hector, Repetto, Maurizio, Liu, Feng and Crozier, Stuart (2016). Intra-coil interactions in split gradient coils in a hybrid MRI-LINAC system. Journal of Magnetic Resonance, 265 (3) 7479461, 52-58. doi: 10.1016/j.jmr.2016.01.013

Intra-coil interactions in split gradient coils in a hybrid MRI-LINAC system

2016

Journal Article

Online dynamic cardiac imaging based on the elastic-net model

Hong, Mingjian, Zhang, Haibiao, Lin, Mengran, Liu, Feng and Ge, Yongxin (2016). Online dynamic cardiac imaging based on the elastic-net model. Inverse Problems in Science and Engineering, 25 (2), 1-14. doi: 10.1080/17415977.2016.1141207

Online dynamic cardiac imaging based on the elastic-net model

2016

Journal Article

Passive shimming of a superconducting magnet using the L1-norm regularized least square algorithm

Kong, Xia, Zhu, Minhua, Xia, Ling, Wang, Qiuliang, Li, Yi, Zhu, Xuchen, Liu, Feng and Crozier, Stuart (2016). Passive shimming of a superconducting magnet using the L1-norm regularized least square algorithm. Journal of Magnetic Resonance, 263, 122-125. doi: 10.1016/j.jmr.2015.11.019

Passive shimming of a superconducting magnet using the L1-norm regularized least square algorithm

2016

Conference Publication

Accelerating dynamic cardiac imaging based on a dual-dictionary learning algorithm

Zhang, Changjiu, Jin, Zhaoyang, Ye, Haihui and Liu, Feng (2016). Accelerating dynamic cardiac imaging based on a dual-dictionary learning algorithm. 2015 8th International Conference on BioMedical Engineering and Informatics, BMEI 2015, Shenyang, China, 14-16 October 2015. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/BMEI.2015.7401473

Accelerating dynamic cardiac imaging based on a dual-dictionary learning algorithm

2016

Journal Article

Simulation of multi-probe radiofrequency ablation guided by optical surgery navigation system under different active modes

Xu, Leyi, Cai, Ken, Yang, Rongqian, Lin, Qinyong, Yue, Hongwei and Liu, Feng (2016). Simulation of multi-probe radiofrequency ablation guided by optical surgery navigation system under different active modes. Computer Assisted Surgery, 21 (1), 107-116. doi: 10.1080/24699322.2016.1210679

Simulation of multi-probe radiofrequency ablation guided by optical surgery navigation system under different active modes

2015

Journal Article

Simulation study of noise reduction methods for a split MRI system using a finite element method

Wang, Y., Liu, F. and Crozier, S. (2015). Simulation study of noise reduction methods for a split MRI system using a finite element method. Medical Physics, 42 (12), 7122-7131. doi: 10.1118/1.4935864

Simulation study of noise reduction methods for a split MRI system using a finite element method

2015

Journal Article

Determination of sample entropy and fuzzy measure entropy parameters for distinguishing congestive heart failure from normal sinus rhythm subjects

Zhao, Lina, Wei, Shoushui, Zhang, Chengqiu, Zhang, Yatao, Jiang, Xinge, Liu, Feng and Liu, Chengyu (2015). Determination of sample entropy and fuzzy measure entropy parameters for distinguishing congestive heart failure from normal sinus rhythm subjects. Entropy, 17 (9), 6270-6288. doi: 10.3390/e17096270

Determination of sample entropy and fuzzy measure entropy parameters for distinguishing congestive heart failure from normal sinus rhythm subjects

2015

Journal Article

Aliasing Artefact Suppression in Compressed Sensing MRI for Random Phase-Encode Undersampling

Yang, Yang, Liu, Feng, Jin Z. and Crozier S. (2015). Aliasing Artefact Suppression in Compressed Sensing MRI for Random Phase-Encode Undersampling. IEEE Transactions on Biomedical Engineering, 62 (9) 7078916, 2215-2223. doi: 10.1109/TBME.2015.2419372

Aliasing Artefact Suppression in Compressed Sensing MRI for Random Phase-Encode Undersampling

2015

Journal Article

Design of shimming rings for small permanent MRI magnet using sensitivity-analysis-based particle swarm optimization algorithm

Cheng, Yiyuan, He, Wei, Xia, Ling and Liu, Feng (2015). Design of shimming rings for small permanent MRI magnet using sensitivity-analysis-based particle swarm optimization algorithm. Journal of Medical and Biological Engineering, 35 (4), 448-454. doi: 10.1007/s40846-015-0051-6

Design of shimming rings for small permanent MRI magnet using sensitivity-analysis-based particle swarm optimization algorithm

2015

Journal Article

A novel passive shimming method for the correction of magnetic fields above the patient bed in MRI

Kong, Xia, Zhu, Minhua, Xia, Ling, Crozier, Stuart, Wang, Qiulang, Ni, Zhipeng and Liu, Feng (2015). A novel passive shimming method for the correction of magnetic fields above the patient bed in MRI. Journal of Magnetic Resonance, 257, 64-69. doi: 10.1016/j.jmr.2015.05.004

A novel passive shimming method for the correction of magnetic fields above the patient bed in MRI

2015

Journal Article

Acoustic analysis for a split MRI system using FE method

Wang, Yaohui, Liu, Feng, Weber, Ewald, Tang, Fangfang, Jin, Jin, Tesiram, Yas and Crozier, Stuart (2015). Acoustic analysis for a split MRI system using FE method. Concepts in Magnetic Resonance Part B: Magnetic Resonance Engineering, 45 (2), 85-96. doi: 10.1002/cmr.b.21283

Acoustic analysis for a split MRI system using FE method

2015

Journal Article

In vivo sensitivity estimation and imaging acceleration with rotating RF coil arrays at 7 Tesla

Li, Mingyan, Jin, Jin, Zuo, Zhentao, Liu, Feng, Trakic, Adnan, Weber, Ewald, Zhuo, Yan, Xue, Rong and Crozier, Stuart (2015). In vivo sensitivity estimation and imaging acceleration with rotating RF coil arrays at 7 Tesla. Journal of Magnetic Resonance, 252, 29-40. doi: 10.1016/j.jmr.2014.12.004

In vivo sensitivity estimation and imaging acceleration with rotating RF coil arrays at 7 Tesla

2015

Conference Publication

A Fast and Practical Imaging Scheme for a Rotating RF Coil at 9.4T by Using Ultra-Short TE Sequence in Radial Trajectory, Investigation of acoustic noise reduction method for MRI-LINAC hybrid system

Li, M., Hugger, T., Weber, E., Jin, J., Liu, F., Ullman, P., Stark, S., Tesiram, Y., Yang, Y., Junge, S. and Crozier, S. (2015). A Fast and Practical Imaging Scheme for a Rotating RF Coil at 9.4T by Using Ultra-Short TE Sequence in Radial Trajectory, Investigation of acoustic noise reduction method for MRI-LINAC hybrid system. International Society for Magnetic Resonance in Medicine (ISMRM), Toronto, Canada, 30 May - 5 June 2015. International Society for Magnetic Resonance in Medicine.

A Fast and Practical Imaging Scheme for a Rotating RF Coil at 9.4T by Using Ultra-Short TE Sequence in Radial Trajectory, Investigation of acoustic noise reduction method for MRI-LINAC hybrid system

2015

Conference Publication

Improving B1+ uniformity using segmented dielectric pads

Destruel, A., Jin, J., Liu, F., Li, M., Weber, E. and Crozier, S. (2015). Improving B1+ uniformity using segmented dielectric pads. International Society for Magnetic Resonance in Medicine (ISMRM), Toronto, Canada, 30 May - 5 June 2015. International Society for Magnetic Resonance in Medicine.

Improving B1+ uniformity using segmented dielectric pads

2015

Conference Publication

MR image reconstruction from under-sampled measurements using local and global sparse representations

Hong, MingJian, Lin, MengRan, Liu, Feng and Ge, YongXin (2015). MR image reconstruction from under-sampled measurements using local and global sparse representations. International Society for Magnetic Resonance in Medicine (ISMRM), Toronto, Canada, 30 May - 5 June 2015. International Society for Magnetic Resonance in Medicine.

MR image reconstruction from under-sampled measurements using local and global sparse representations

2015

Conference Publication

Feasibility test of non-iterative reconstruction for high spatiotemporal resolution DCE, investigation of acoustic noise reduction method for MRI-LINAC hybrid system

Chen, Z., Yang, M., Kang, L. and Liu, F. (2015). Feasibility test of non-iterative reconstruction for high spatiotemporal resolution DCE, investigation of acoustic noise reduction method for MRI-LINAC hybrid system. International Society for Magnetic Resonance in Medicine (ISMRM), Toronto, Canada, 30 May - 5 June 2015. International Society for Magnetic Resonance in Medicine.

Feasibility test of non-iterative reconstruction for high spatiotemporal resolution DCE, investigation of acoustic noise reduction method for MRI-LINAC hybrid system

2015

Journal Article

Compressed sensing MRI via two-stage reconstruction

Yang, Yang, Liu, Feng, Xu, Wenlong and Crozier, Stuart (2015). Compressed sensing MRI via two-stage reconstruction. IEEE Transactions on Biomedical Engineering, 62 (1) 6862879, 110-118. doi: 10.1109/TBME.2014.2341621

Compressed sensing MRI via two-stage reconstruction

2015

Conference Publication

Investigation of acoustic noise reduction method for MRI-LINAC hybrid system

Wang, Y. H., Liu, F., Weber, E. and Crozier, S. (2015). Investigation of acoustic noise reduction method for MRI-LINAC hybrid system. International Society for Magnetic Resonance in Medicine (ISMRM), Toronto, Canada, 30 May - 5 June 2015. International Society of Magnetic Resonance in Medicine.

Investigation of acoustic noise reduction method for MRI-LINAC hybrid system

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
  • 2022 - 2025
    Evaluation of 7T 8-channel MRI coil for imaging of the human spine
    Aix-Marseille University
    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
  • 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

Before you email them, read our advice on how to contact 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

    Passive shimming and electromagnetic contrast imaging at ultrahigh field MRI

    Principal Advisor

  • Doctor Philosophy

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

    Principal Advisor

    Other advisors: Associate Professor Kai-Hsiang Chuang

  • Doctor Philosophy

    Diagnosis of Arrhythmia using ECG signal classification by neural networks

    Principal Advisor

  • Doctor Philosophy

    Combined Compressed sensing and machine learning/deep learning methods for rapid MRI

    Principal Advisor

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

  • 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

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

    Principal Advisor

  • Doctor Philosophy

    Generalizable and robust quantitative susceptibility mapping using 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

    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

  • Doctor Philosophy

    MRI methods development through deep learning

    Associate Advisor

    Other advisors: 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)

Need help?

For help with finding experts, story ideas and media enquiries, contact our Media team:

communications@uq.edu.au