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

482 works between 1997 and 2025
All (482) Journal Article (309) Conference Publication (170) Other Outputs (3)

201 - 220 of 482 works

2017

Journal Article

Improved k - t PCA algorithm using artificial sparsity in dynamic MRI

Wang, Yiran, Chen, Zhifeng, Wang, Jing, Yuan, Lixia, Xia, Ling and Liu, Feng (2017). Improved k - t PCA algorithm using artificial sparsity in dynamic MRI. Computational and Mathematical Methods in Medicine, 2017 4816024, 4816024-12. doi: 10.1155/2017/4816024

Improved k - t PCA algorithm using artificial sparsity in dynamic MRI

2017

Conference Publication

Comparison of four recovery algorithms used in compressed sensing for ECG signal processing

Zhang, Zhimin , Wei, Shoushui , Wei, Dingwen, Li, Liping , Liu, Feng and Liu, Chengyu (2017). Comparison of four recovery algorithms used in compressed sensing for ECG signal processing. 43rd Computing in Cardiology Conference, CinC 2016, Vancouver, Canada, 11 - 14 September 2016. Piscataway, NJ, United States: Institute for Electrical and Electronics Engineers. doi: 10.22489/cinc.2016.116-226

Comparison of four recovery algorithms used in compressed sensing for ECG signal processing

2016

Journal Article

An improved asymmetric gradient coil design for high-resolution MRI head imaging

Tang, Fangfang , Liu, Feng, Freschi, Fabio, Li, Yu, Repetto, Maurizio, Giaccone, Luca, Wang, Yaohui and Crozier, Stuart  (2016). An improved asymmetric gradient coil design for high-resolution MRI head imaging. Physics in Medicine and Biology, 61 (24), 8875-8889. doi: 10.1088/1361-6560/61/24/8875

An improved asymmetric gradient coil design for high-resolution MRI head imaging

2016

Journal Article

The design of decoupled even-order zonal superconducting shim coils for a 9.4 T whole-body MRI

Zhu, Xuchen, Wang, Qiuliang, Li, Yi, Hu, Yang, Chen, Wenbo and Liu, Feng (2016). The design of decoupled even-order zonal superconducting shim coils for a 9.4 T whole-body MRI. IEEE Transactions on Applied Superconductivity, 26 (8) 7539277, 1-8. doi: 10.1109/TASC.2016.2598775

The design of decoupled even-order zonal superconducting shim coils for a 9.4 T whole-body MRI

2016

Journal Article

Pseudo-Polar Fourier Transform based Compressed Sensing MRI

Yang, Yang, Liu, Feng, Li, Mingyan, Jin, Jin, Weber, Ewald, Liu, Qinghuo and Crozier, Stuart (2016). Pseudo-Polar Fourier Transform based Compressed Sensing MRI. IEEE Transactions on Biomedical Engineering, 99 (4) 7488260, 816-825. doi: 10.1109/TBME.2016.2578930

Pseudo-Polar Fourier Transform based Compressed Sensing MRI

2016

Journal Article

Dynamic updating atlas for heart segmentation with a nonlinear field-based model

Cai, Ken, Yang, Rongqian, Yue, Hongwei, Li, Lihua, Ou, Shanxing and Liu, Feng (2016). Dynamic updating atlas for heart segmentation with a nonlinear field-based model. International Journal of Medical Robotics and Computer Assisted Surgery, 13 (3) e1785, 1-10. doi: 10.1002/rcs.1785

Dynamic updating atlas for heart segmentation with a nonlinear field-based model

2016

Journal Article

A large-scale measurement of dielectric properties of normal and malignant colorectal tissues obtained from cancer surgeries at Larmor frequencies

Li, Zhou, Deng, Guanhua, Li, Zhe, Xin, Sherman Xuegang, Duan, Song, Lan, Maoying, Zhang, Sa, Gao, Yixin, He, Jun, Zhang, Songtao, Tang, Hongming, Wang, Weiwei, Han, Shuai, Yang, Qing X., Zhuang, Ling, Hu, Jiani and Liu, Feng (2016). A large-scale measurement of dielectric properties of normal and malignant colorectal tissues obtained from cancer surgeries at Larmor frequencies. Medical Physics, 43 (11), 5991-5997. doi: 10.1118/1.4964460

A large-scale measurement of dielectric properties of normal and malignant colorectal tissues obtained from cancer surgeries at Larmor frequencies

2016

Journal Article

High field superconducting magnet technologies for magnetic resonance imaging

Wang, Q., Li, Y., Yang, W., Dong, Z., Zhu, X., Hu, G., Hu, Y., Ni, Z., Xu, J., Cheng, J., Wang, H., Dai, Y., Yan, L., Liu, F., Xia, L., Cheng, W., Mu, X., Zheng, J., Niu, C., Wang, L., Zhu, G., Sun, W., Zhao, B., Li, X., Liu, J. and Yan, C. (2016). High field superconducting magnet technologies for magnetic resonance imaging. IEEE Transactions on Applied Superconductivity, 26 (7) 7480860, 1-7. doi: 10.1109/TASC.2016.2574357

High field superconducting magnet technologies for magnetic resonance imaging

2016

Journal Article

Asymmetric gradient coil design for use in a short, open bore magnetic resonance imaging scanner

Wang, Yaohui, Liu, Feng, Li, Yu, Tang, Fangfang and Crozier, Stuart (2016). Asymmetric gradient coil design for use in a short, open bore magnetic resonance imaging scanner. Journal of Magnetic Resonance, 269, 203-212. doi: 10.1016/j.jmr.2016.06.015

Asymmetric gradient coil design for use in a short, open bore magnetic resonance imaging scanner

2016

Journal Article

Numerical assessment of the reduction of specific absorption rate by adding high dielectric materials for fetus MRI at 3 T

Luo, Minmin, Hu, Can, Zhuang, Yayun, Chen, Wufan, Liu, Feng and Xin, Sherman Xuegang (2016). Numerical assessment of the reduction of specific absorption rate by adding high dielectric materials for fetus MRI at 3 T. Biomedizinische Technik, 61 (4), 455-461. doi: 10.1515/bmt-2015-0171

Numerical assessment of the reduction of specific absorption rate by adding high dielectric materials for fetus MRI at 3 T

2016

Journal Article

Quantitative analysis of the reconstruction errors of the currently popular algorithm of magnetic resonance electrical property tomography at the interfaces of adjacent tissues

Duan, Song, Xu, Chao, Deng, Guanhua, Wang, Jiajia, Liu, Feng and Xin, Sherman Xuegang (2016). Quantitative analysis of the reconstruction errors of the currently popular algorithm of magnetic resonance electrical property tomography at the interfaces of adjacent tissues. NMR in Biomedicine, 29 (6), 744-750. doi: 10.1002/nbm.3522

Quantitative analysis of the reconstruction errors of the currently popular algorithm of magnetic resonance electrical property tomography at the interfaces of adjacent tissues

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

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

    Innovative RF Coil Designs and Metamaterial Applications for Ultra-High Field MRI

    Principal Advisor

    Other advisors: Emeritus Professor Stuart Crozier, Dr Lei Guo

  • Doctor Philosophy

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

    Principal Advisor

    Other advisors: Associate Professor Kai-Hsiang Chuang

  • Doctor Philosophy

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

    Principal Advisor

    Other advisors: Dr Hongfu Sun

  • Doctor Philosophy

    Innovative RF Coil Designs and Metamaterial Applications for Ultra-High Field MRI

    Principal Advisor

    Other advisors: Emeritus Professor Stuart Crozier, Dr Lei Guo

  • Doctor Philosophy

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

    Principal Advisor

  • Doctor Philosophy

    The design of metamaterial RF shield to reduce specific absorption rate and improve B1 efficiency for ultra-high field MRI

    Principal Advisor

    Other advisors: Emeritus Professor Stuart Crozier, Dr Lei Guo

  • Doctor Philosophy

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

    Principal Advisor

  • Doctor Philosophy

    Diagnosis of Arrhythmia using ECG signal classification by neural networks

    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

    AI-empowered super-resolution MRI

    Principal Advisor

  • Doctor Philosophy

    Advance low-field MRI with deep learning fused techonologies

    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

    MRI methods development through deep learning

    Associate Advisor

    Other advisors: Dr Hongfu Sun

  • Doctor Philosophy

    MR image processing through advanced optimization 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

    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

    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

    Generalizable and robust quantitative susceptibility mapping using 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)

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