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

422 works between 1997 and 2024
All (422) Journal Article (255) Conference Publication (164) Other Outputs (3)

41 - 60 of 422 works

2023

Journal Article

Measurement of the B0 lifetime and flavor-oscillation frequency using hadronic decays reconstructed in 2019-2021 Belle II data

Abudinen, F., Adachi, I., Aggarwal, L., Ahmed, H., Aihara, H., Akopov, N., Aloisio, A., Ky, N. Anh, Asner, D. M., Atmacan, H., Aushev, T., Aushev, V., Bae, H., Bahinipati, S., Bambade, P., Banerjee, Sw, Bansal, S., Barrett, M., Baudot, J., Bauer, M., Baur, A., Beaubien, A., Becker, J., Bennett, J. V., Bernieri, E., Bernlochner, F. U., Bertacchi, V., Bertemes, M., Bertholet, E. ... Zlebcik, R. (2023). Measurement of the B0 lifetime and flavor-oscillation frequency using hadronic decays reconstructed in 2019-2021 Belle II data. Physical Review D, 107 (9) L091102, 1-9. doi: 10.1103/PhysRevD.107.L091102

Measurement of the B0 lifetime and flavor-oscillation frequency using hadronic decays reconstructed in 2019-2021 Belle II data

2023

Journal Article

Distortion‐corrected image reconstruction with deep learning on an MRI‐Linac

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

Distortion‐corrected image reconstruction with deep learning on an MRI‐Linac

2023

Journal Article

High-performance shim coil design and engineering optimization for use in an extremely high field superconducting magnet

Zheng, Yijie, Wang, Yaohui, Liu, Feng, Yan, Ming and Wang, Qiuliang (2023). High-performance shim coil design and engineering optimization for use in an extremely high field superconducting magnet. Review of Scientific Instruments, 94 (4) 044712, 1-8. doi: 10.1063/5.0137337

High-performance shim coil design and engineering optimization for use in an extremely high field superconducting magnet

2023

Journal Article

Probe beam influence on spin polarization in spin-exchange relaxation-free co-magnetometers

Wei, Yao, Xing, Li, Zhai, Yueyang, Fan, Wenfeng, Fang, Chi, Liu, Feng and Quan, Wei (2023). Probe beam influence on spin polarization in spin-exchange relaxation-free co-magnetometers. Journal of Physics D: Applied Physics, 56 (13) 135001, 1-9. doi: 10.1088/1361-6463/acbd60

Probe beam influence on spin polarization in spin-exchange relaxation-free co-magnetometers

2023

Journal Article

Affine transformation edited and refined deep neural network for quantitative susceptibility mapping

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

Affine transformation edited and refined deep neural network for quantitative susceptibility mapping

2023

Journal Article

Atrial fibrillation classification based on the 2D representation of minimal subset ECG and a non-deep neural network

Zhang, Hua, Liu, Chengyu, Tang, Fangfang, Li, Mingyan, Zhang, Dongxia, Xia, Ling, Crozier, Stuart, Gan, Hongping, Zhao, Nan, Xu, Wenlong and Liu, Feng (2023). Atrial fibrillation classification based on the 2D representation of minimal subset ECG and a non-deep neural network. Frontiers in Physiology, 14 1070621, 1070621. doi: 10.3389/fphys.2023.1070621

Atrial fibrillation classification based on the 2D representation of minimal subset ECG and a non-deep neural network

2023

Journal Article

HFIST-Net: High-Throughput Fast Iterative Shrinkage Thresholding Network for accelerating MR image reconstruction

Geng, Chenghu, Jiang, Mingfeng, Fang, Xian, Li, Yang, Jin, Guangri, Chen, Aixi and Liu, Feng (2023). HFIST-Net: High-Throughput Fast Iterative Shrinkage Thresholding Network for accelerating MR image reconstruction. Computer Methods and Programs in Biomedicine, 232 107440, 1-8. doi: 10.1016/j.cmpb.2023.107440

HFIST-Net: High-Throughput Fast Iterative Shrinkage Thresholding Network for accelerating MR image reconstruction

2023

Journal Article

A hybrid FDTD/MoM algorithm with a non-uniform grid for MRI RF coil design

Liu, Yang, Wang, Qiuliang and Liu, Feng (2023). A hybrid FDTD/MoM algorithm with a non-uniform grid for MRI RF coil design. Magnetic Resonance Imaging, 96, 75-84. doi: 10.1016/j.mri.2022.10.008

A hybrid FDTD/MoM algorithm with a non-uniform grid for MRI RF coil design

2023

Journal Article

3D‐EPI blip‐up/down acquisition ( BUDA ) with CAIPI and joint H ankel structured low‐rank reconstruction for rapid distortion‐free high‐resolution T2* mapping

Chen, Zhifeng, Liao, Congyu, Cao, Xiaozhi, Poser, Benedikt A., Xu, Zhongbiao, Lo, Wei‐Ching, Wen, Manyi, Cho, Jaejin, Tian, Qiyuan, Wang, Yaohui, Feng, Yanqiu, Xia, Ling, Chen, Wufan, Liu, Feng and Bilgic, Berkin (2023). 3D‐EPI blip‐up/down acquisition ( BUDA ) with CAIPI and joint H ankel structured low‐rank reconstruction for rapid distortion‐free high‐resolution T2* mapping. Magnetic Resonance in Medicine, 89 (5), 1961-1974. doi: 10.1002/mrm.29578

3D‐EPI blip‐up/down acquisition ( BUDA ) with CAIPI and joint H ankel structured low‐rank reconstruction for rapid distortion‐free high‐resolution T2* mapping

2023

Conference Publication

QSM from the raw phase using an end-to-end neural network

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

QSM from the raw phase using an end-to-end neural network

2023

Journal Article

Gradient coil design with enhanced shielding constraint for a cryogen-free superconducting MRI system

Wang, Yaohui, Wang, Weimin, Liu, Hui, Chen, Shunzhong, Liu, Feng and Wang, Qiuliang (2023). Gradient coil design with enhanced shielding constraint for a cryogen-free superconducting MRI system. Magnetic Resonance Letters, 4 (1) 100086, 100086. doi: 10.1016/j.mrl.2023.09.001

Gradient coil design with enhanced shielding constraint for a cryogen-free superconducting MRI system

2023

Conference Publication

Tuberculosis detection based on cough sounds: a multi-model voting mechanism

Bao, Xiaofan, Xu, Wenlong, Pan, Chen, Liu, Wenlong, Lou, Xiaomin, Chen, Yuanyuan, Zhao, Xiaoqiang, Zhang, Chenlu and Liu, Feng (2023). Tuberculosis detection based on cough sounds: a multi-model voting mechanism. 16th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), Taizhou, China, 28-30 October 2023. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/CISP-BMEI60920.2023.10373284

Tuberculosis detection based on cough sounds: a multi-model voting mechanism

2023

Journal Article

Three-dimensional echo-shifted EPI with simultaneous blip-up and blip-down acquisitions for correcting geometric distortion

Sun, Kaibao, Chen, Zhifeng, Dan, Guangyu, Luo, Qingfei, Yan, Lirong, Liu, Feng and Zhou, Xiaohong Joe (2023). Three-dimensional echo-shifted EPI with simultaneous blip-up and blip-down acquisitions for correcting geometric distortion. Magnetic Resonance in Medicine, 90 (6), 2375-2387. doi: 10.1002/mrm.29828

Three-dimensional echo-shifted EPI with simultaneous blip-up and blip-down acquisitions for correcting geometric distortion

2023

Conference Publication

Exposure of infants in baby gradient coils

Tang, Fangfang, Giaccone, Luca, Freschi, Fabio, Crozier, Stuart and Liu, Feng (2023). Exposure of infants in baby gradient coils. ISMRM Annual Meeting, London, United Kingdom, 7-12 May 2022. Concord, CA, United States: ISMRM. doi: 10.58530/2022/4372

Exposure of infants in baby gradient coils

2023

Journal Article

Distributed estimation with adaptive cluster learning over asynchronous data fusion

Hua, Yi, Gan, Hongping, Wan, Fangyi, Qing, Xinlin and Liu, Feng (2023). Distributed estimation with adaptive cluster learning over asynchronous data fusion. IEEE Transactions on Aerospace and Electronic Systems, 59 (5), 1-12. doi: 10.1109/taes.2023.3253085

Distributed estimation with adaptive cluster learning over asynchronous data fusion

2022

Journal Article

A novel passive shimming scheme using explicit control of magnetic field qualities with minimal use of ferromagnetic materials

Wang, Yaohui, Wang, Qiuliang, Chen, Zhifeng, Liu, Yang and Liu, Feng (2022). A novel passive shimming scheme using explicit control of magnetic field qualities with minimal use of ferromagnetic materials. Magnetic Resonance in Medicine, 88 (6), 2732-2744. doi: 10.1002/mrm.29419

A novel passive shimming scheme using explicit control of magnetic field qualities with minimal use of ferromagnetic materials

2022

Journal Article

Detecting depression using single-channel EEG and graph methods

Zhu, Guohun, Qiu, Tong, Ding, Yi, Gao, Shang, Zhao, Nan, Liu, Feng, Zhou, Xujuan and Gururajan, Raj (2022). Detecting depression using single-channel EEG and graph methods. Mathematics, 10 (22) 4177, 1-9. doi: 10.3390/math10224177

Detecting depression using single-channel EEG and graph methods

2022

Journal Article

A forced cough sound based pulmonary function assessment method by using machine learning

Xu, Wenlong, He, Guoqiang, Pan, Chen, Shen, Dan, Zhang, Ning, Jiang, Peirong, Liu, Feng and Chen, Jingjing (2022). A forced cough sound based pulmonary function assessment method by using machine learning. Frontiers in Public Health, 10 1015876, 1-10. doi: 10.3389/fpubh.2022.1015876

A forced cough sound based pulmonary function assessment method by using machine learning

2022

Journal Article

Analysis and suppression of thermal magnetic noise of ferrite in the SERF co-magnetometer

Pang, Haoying, Liu, Feng, Fan, Wengfeng, Wu, Jiaqi, Yuan, Qi, Wu, Zhihong and Quan, Wei (2022). Analysis and suppression of thermal magnetic noise of ferrite in the SERF co-magnetometer. Materials, 15 (19) 6971, 1-10. doi: 10.3390/ma15196971

Analysis and suppression of thermal magnetic noise of ferrite in the SERF co-magnetometer

2022

Journal Article

Instant tissue field and magnetic susceptibility mapping from MRI raw phase using Laplacian enhanced deep neural networks

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

Instant tissue field and magnetic susceptibility mapping from MRI raw phase using Laplacian enhanced deep neural networks

Current funding

  • 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

    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

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

    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

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

    Principal Advisor

    Other advisors: Associate Professor Kai-Hsiang Chuang

  • Doctor Philosophy

    Passive shimming and electromagnetic contrast imaging at ultrahigh field MRI

    Principal Advisor

  • Doctor Philosophy

    Advance low-field MRI with deep learning fused techonologies

    Principal Advisor

  • Doctor Philosophy

    AI-empowered super-resolution MRI

    Principal Advisor

  • Doctor Philosophy

    Diagnosis of Arrhythmia using ECG signal classification by neural networks

    Principal Advisor

  • Doctor Philosophy

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

    Principal Advisor

  • Doctor Philosophy

    MR image processing through advanced optimisation techniques and deep learning

    Associate Advisor

    Other advisors: 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 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

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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