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)

21 - 40 of 482 works

2024

Journal Article

Electromagnetic design and mechanical analysis of a 28.2 T/1.2 GHz high field NMR magnet

Ren, Yong, Liu, Feng and Li, Da (2024). Electromagnetic design and mechanical analysis of a 28.2 T/1.2 GHz high field NMR magnet. IEEE Transactions on Applied Superconductivity, 34 (7) 4301507. doi: 10.1109/TASC.2024.3418385

Electromagnetic design and mechanical analysis of a 28.2 T/1.2 GHz high field NMR magnet

2024

Journal Article

Passive shimming optimization method of MRI based on genetic algorithm-sequential quadratic programming 

Zhao, Jie, Liu, Feng, Xia, Ling and Fan, Yifeng (2024). Passive shimming optimization method of MRI based on genetic algorithm-sequential quadratic programming . Zhejiang Daxue Xuebao (Gongxue Ban), 58 (6), 1305-1314. doi: 10.3785/j.issn.1008-973X.2024.06.020

Passive shimming optimization method of MRI based on genetic algorithm-sequential quadratic programming 

2024

Conference Publication

Fast controllable diffusion models for undersampled MRI reconstruction

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

Fast controllable diffusion models for undersampled MRI reconstruction

2024

Conference Publication

Single image compressed sensing MRI via a self-supervised deep denoising approach

Bran Lorenzana, Marlon, Liu, Feng and Chandra, Shekhar S. (2024). Single image compressed sensing MRI via a self-supervised deep denoising approach. 2024 IEEE International Symposium on Biomedical Imaging (ISBI), Athens, Greece, 27-30 May 2024. Piscataway, NJ, United States: IEEE. doi: 10.1109/isbi56570.2024.10635749

Single image compressed sensing MRI via a self-supervised deep denoising approach

2024

Journal Article

Feature fusion method for pulmonary tuberculosis patient detection based on cough sound

Xu, Wenlong, Bao, Xiaofan, Lou, Xiaomin, Liu, Xiaofang, Chen, Yuanyuan, Zhao, Xiaoqiang, Zhang, Chenlu, Pan, Chen, Liu, Wenlong and Liu, Feng (2024). Feature fusion method for pulmonary tuberculosis patient detection based on cough sound. PLoS One, 19 (5) e0302651, 1-12. doi: 10.1371/journal.pone.0302651

Feature fusion method for pulmonary tuberculosis patient detection based on cough sound

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

Quantitative susceptibility mapping through model-based deep image prior (MoDIP)

2024

Journal Article

A cross-domain complex convolution neural network for undersampled magnetic resonance image reconstruction

Yuan, Tengfei, Yang, Jie, Chi, Jieru, Yu, Teng and Liu, Feng (2024). A cross-domain complex convolution neural network for undersampled magnetic resonance image reconstruction. Magnetic Resonance Imaging, 108, 86-97. doi: 10.1016/j.mri.2024.02.004

A cross-domain complex convolution neural network for undersampled magnetic resonance image reconstruction

2024

Journal Article

Plug-and-Play latent feature editing for orientation-adaptive quantitative susceptibility mapping neural networks

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, 1-11. doi: 10.1016/j.media.2024.103160

Plug-and-Play latent feature editing for orientation-adaptive quantitative susceptibility mapping neural networks

2024

Journal Article

Magnetic resonance spectroscopy spectral registration using deep learning

Ma, David J. J., Yang, Yanting, Harguindeguy, Natalia, Tian, Ye, Small, Scott A., Liu, Feng, Rothman, Douglas L. and Guo, Jia (2024). Magnetic resonance spectroscopy spectral registration using deep learning. Journal of Magnetic Resonance Imaging, 59 (3), 964-975. doi: 10.1002/jmri.28868

Magnetic resonance spectroscopy spectral registration using deep learning

2024

Journal Article

Constructing diatomic catalyst on MoSSe achieves ultra-low overpotential for nitrogen fixation: First-principles study

Xu, Ying, Bao, An Yu, Xiong, Zheng Yun, Liu, Feng and Sheng, Wei (2024). Constructing diatomic catalyst on MoSSe achieves ultra-low overpotential for nitrogen fixation: First-principles study. Applied Physics Letters, 124 (9) 093901. doi: 10.1063/5.0194388

Constructing diatomic catalyst on MoSSe achieves ultra-low overpotential for nitrogen fixation: First-principles study

2024

Journal Article

Ability of dynamic gadoxetic acid-enhanced magnetic resonance imaging combined with water-specific T1 mapping to reflect inflammation in a rat model of early-stage nonalcoholic steatohepatitis

Wan, Qian, Peng, Hao, Liu, Feng, Liu, Xiaoyi, Cheng, Chuanli, Tie, Changjun, Deng, Jie, Lyu, Jianxun, Jia, Yizhen, Wang, Yi, Zheng, Hairong, Liang, Dong, Liu, Xin and Zou, Chao (2024). Ability of dynamic gadoxetic acid-enhanced magnetic resonance imaging combined with water-specific T1 mapping to reflect inflammation in a rat model of early-stage nonalcoholic steatohepatitis. Quantitative Imaging in Medicine and Surgery, 14 (2), 1-12. doi: 10.21037/qims-23-482

Ability of dynamic gadoxetic acid-enhanced magnetic resonance imaging combined with water-specific T1 mapping to reflect inflammation in a rat model of early-stage nonalcoholic steatohepatitis

2024

Journal Article

A hybrid 2D-FDTD/3D-MoM method used for the analysis of MRI RF coils

Liu, Yang, Wang, Qiuliang and Liu, Feng (2024). A hybrid 2D-FDTD/3D-MoM method used for the analysis of MRI RF coils. Magnetic Resonance Imaging, 106, 77-84. doi: 10.1016/j.mri.2023.11.005

A hybrid 2D-FDTD/3D-MoM method used for the analysis of MRI RF coils

2024

Journal Article

Pediatric Pulmonary Function Assessment Using Artificial Intelligence with Cough Sounds

Xu, Wenlong, Bai, Junrong, Chen, Yunlong, Dai, Ling, Shen, Dan, Bao, Xiaofan, Pan, Chen and Liu, Feng (2024). Pediatric Pulmonary Function Assessment Using Artificial Intelligence with Cough Sounds. Indian Journal of Pediatrics, 91 (8), 857-858. doi: 10.1007/s12098-024-05035-y

Pediatric Pulmonary Function Assessment Using Artificial Intelligence with Cough Sounds

2024

Journal Article

Probing underlying biophysical mechanisms of electrical properties change by pathogenesis at the microscopic cellular level

Xu, Guofang, Liu, Henghui, Ren, Yinhao, Liao, Yupeng, Liu, Feng, Nan, Xiang and Han, Jijun (2024). Probing underlying biophysical mechanisms of electrical properties change by pathogenesis at the microscopic cellular level. Applied Physics Letters, 124 (3) 033701. doi: 10.1063/5.0184776

Probing underlying biophysical mechanisms of electrical properties change by pathogenesis at the microscopic cellular level

2024

Journal Article

Accurate magnetization modeling in multi-dimensional applications

Wang, Yaohui, Yang, Wenhui, Liu, Feng and Wang, Qiuliang (2024). Accurate magnetization modeling in multi-dimensional applications. Journal of Applied Physics, 135 (2) 023901. doi: 10.1063/5.0173725

Accurate magnetization modeling in multi-dimensional applications

2024

Journal Article

Electromagnetic Design of a 0.5 T REBCO MRI magnet for Brain MRI imaging

Li, Da, Ren, Yong and Liu, Feng (2024). Electromagnetic Design of a 0.5 T REBCO MRI magnet for Brain MRI imaging. IEEE Transactions on Applied Superconductivity, 34 (7) 4403207, 1-7. doi: 10.1109/tasc.2024.3426543

Electromagnetic Design of a 0.5 T REBCO MRI magnet for Brain MRI imaging

2024

Journal Article

Asymmetrical planar folded dipole antennas for human body MRI at 7 T

Chen, Haiwei, Guo, Lei, Lou, Feiyang, Gao, Yang, Quan, Zhiyan, Liu, Chunyi, Boulant, Nicolas, Liu, Feng and Zhang, Xiaotong (2024). Asymmetrical planar folded dipole antennas for human body MRI at 7 T. IEEE Transactions on Antennas and Propagation, PP (99), 1-1. doi: 10.1109/tap.2024.3513639

Asymmetrical planar folded dipole antennas for human body MRI at 7 T

2024

Conference Publication

QSM Reconstruction of Arbitrary Dipole Orientations using an End-to-end Neural Network via Latent Feature Editing

Gao, 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

QSM Reconstruction of Arbitrary Dipole Orientations using an End-to-end Neural Network via Latent Feature Editing

2024

Journal Article

Perceptual contrast and residual self-attention generative adversarial network-based for highly under-sampled MRI reconstruction

Lin, Suzhen, Fan, Xiaoyu, Ma, Fengfei, Liu, Feng, Wang, Lifang, Wang, Yanbo and Qiu, Hualu (2024). Perceptual contrast and residual self-attention generative adversarial network-based for highly under-sampled MRI reconstruction. Digital Signal Processing, 144 104277, 1-13. doi: 10.1016/j.dsp.2023.104277

Perceptual contrast and residual self-attention generative adversarial network-based for highly under-sampled MRI reconstruction

2024

Journal Article

Image Reconstruction with B<sub>0</sub> Inhomogeneity using a Deep Unrolled Network on an Open-bore MRI-Linac

Shan, Shanshan, Gao, Yang, Waddington, David, Chen, Hongli, Whelan, Brendan, Liu, Paul, Wang, Yaohui, Liu, Chunyi, Gan, Hongping, Gao, Mingyuan and Liu, Feng (2024). Image Reconstruction with B0 Inhomogeneity using a Deep Unrolled Network on an Open-bore MRI-Linac. IEEE Transactions on Instrumentation and Measurement, 73 2534109, 1-1. doi: 10.1109/tim.2024.3481545

Image Reconstruction with B<sub>0</sub> Inhomogeneity using a Deep Unrolled Network on an Open-bore MRI-Linac

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

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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

    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

    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

    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

    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

    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

    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 optimization 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

  • 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)

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