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)

1 - 20 of 422 works

2024

Journal Article

LUCMT: Learnable under-sampling and reconstructed network with cross multi-head attention transformer for accelerating MR image reconstruction

Yang, Ziqi, Jiang, Mingfeng, Ruan, Dongshen, Li, Yang, Tan, Tao, Huang, Sumei and Liu, Feng (2024). LUCMT: Learnable under-sampling and reconstructed network with cross multi-head attention transformer for accelerating MR image reconstruction. Computer Methods and Programs in Biomedicine, 255 108359, 108359. doi: 10.1016/j.cmpb.2024.108359

LUCMT: Learnable under-sampling and reconstructed network with cross multi-head attention transformer for accelerating MR image reconstruction

2024

Journal Article

MTC-CSNet: marrying transformer and convolution for image compressed sensing

Shen, Minghe, Gan, Hongping, Ma, Chunyan, Ning, Chao, Li, Hongqi and Liu, Feng (2024). MTC-CSNet: marrying transformer and convolution for image compressed sensing. IEEE Transactions on Cybernetics, 54 (9), 4949-4961. doi: 10.1109/tcyb.2024.3363748

MTC-CSNet: marrying transformer and convolution for image compressed sensing

2024

Journal Article

Mitogenomes of museum specimens provide new insight into species classification and recently reduced diversity of highly endangered <i>Nomascus</i> gibbons

LIU, Siqiong, LI, Kexin, ZHENG, Yuxin, XUE, Jiayang, WANG, Sheng, LI, Song, CAO, Peng, LIU, Feng, DAI, Qingyan, FENG, Xiaotian, YANG, Ruowei, PING, Wanjing, WU, Dongdong, FAN, Pengfei, FU, Qiaomei and CHEN, Zehui (2024). Mitogenomes of museum specimens provide new insight into species classification and recently reduced diversity of highly endangered Nomascus gibbons. Integrative Zoology. doi: 10.1111/1749-4877.12878

Mitogenomes of museum specimens provide new insight into species classification and recently reduced diversity of highly endangered <i>Nomascus</i> gibbons

2024

Journal Article

Active shimming for a 25 T NMR superconducting magnet by spectrum convergence method

Chen, Haoran, Wang, Yaohui, Wang, Wenchen, Zhou, Guyue, Wu, Pengfei, Qu, Hongyi, Liu, Jianhua, Li, Liang and Liu, Feng (2024). Active shimming for a 25 T NMR superconducting magnet by spectrum convergence method. Journal of Magnetic Resonance, 364 107711, 107711. doi: 10.1016/j.jmr.2024.107711

Active shimming for a 25 T NMR superconducting magnet by spectrum convergence method

2024

Journal Article

Solar-powered mixed-linker metal-organic frameworks for water harvesting from arid air

Yan, Xueli, Xue, Fei, Zhang, Chunyang, Peng, Hao, Huang, Jie, Liu, Feng, Lu, Kejian, Wang, Ruizhe, Shi, Jinwen, Li, Naixu, Chen, Wenshuai and Liu, Maochang (2024). Solar-powered mixed-linker metal-organic frameworks for water harvesting from arid air. Ecomat, 6 (7). doi: 10.1002/eom2.12473

Solar-powered mixed-linker metal-organic frameworks for water harvesting from arid air

2024

Journal Article

Passive shimming optimization method of MRI based on genetic algorithm-sequential quadratic programming 基 于 遗 传 算 法 -序 列 二 次 规 划 的 磁 共 振被 动 匀 场 优 化 方 法

Zhao, Jie, Liu, Feng, Xia, Ling and Fan, Yifeng (2024). Passive shimming optimization method of MRI based on genetic algorithm-sequential quadratic programming 基 于 遗 传 算 法 -序 列 二 次 规 划 的 磁 共 振被 动 匀 场 优 化 方 法. Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science), 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 基 于 遗 传 算 法 -序 列 二 次 规 划 的 磁 共 振被 动 匀 场 优 化 方 法

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, e0302651. 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, 103160. doi: 10.1016/j.media.2024.103160

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

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

Time-domain sparsity-based bearing fault diagnosis methods using pulse signal-to-noise ratio

Zhang, Chi, Wei, Shaoming, Dong, Ge, Zeng, Yajun, Zhu, Guohun, Zhou, Xujuan and Liu, Feng (2024). Time-domain sparsity-based bearing fault diagnosis methods using pulse signal-to-noise ratio. IEEE Transactions on Instrumentation and Measurement, 73 (99) 3516804, 1-4. doi: 10.1109/tim.2024.3375978

Time-domain sparsity-based bearing fault diagnosis methods using pulse signal-to-noise ratio

2024

Journal Article

NesTD-Net: deep NESTA-inspired unfolding network with dual-path deblocking structure for image compressive sensing

Gan, Hongping, Guo, Zhen and Liu, Feng (2024). NesTD-Net: deep NESTA-inspired unfolding network with dual-path deblocking structure for image compressive sensing. IEEE Transactions on Image Processing, 33, 1923-1937. doi: 10.1109/tip.2024.3371351

NesTD-Net: deep NESTA-inspired unfolding network with dual-path deblocking structure for image compressive sensing

2024

Journal Article

Electromagnetic Design and Mechanical Analysis of a 28.2 T&#x002F;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&#x002F;1.2 GHz High Field NMR Magnet. IEEE Transactions on Applied Superconductivity, 34 (7) 4301507, 1-7. doi: 10.1109/TASC.2024.3418385

Electromagnetic Design and Mechanical Analysis of a 28.2 T&#x002F;1.2 GHz High Field NMR Magnet

2024

Journal Article

Using Adaptive Imaging Parameters to Improve PEGylated Ultrasmall Iron Oxide Nanoparticles-Enhanced Magnetic Resonance Angiography

Li, Cang, Shan, Shanshan, Chen, Lei, Afshari, Mohammad Javad, Wang, Hongzhao, Lu, Kuan, Kou, Dandan, Wang, Ning, Gao, Yang, Liu, Chunyi, Zeng, Jianfeng, Liu, Feng and Gao, Mingyuan (2024). Using Adaptive Imaging Parameters to Improve PEGylated Ultrasmall Iron Oxide Nanoparticles-Enhanced Magnetic Resonance Angiography. Advanced Science. doi: 10.1002/advs.202405719

Using Adaptive Imaging Parameters to Improve PEGylated Ultrasmall Iron Oxide Nanoparticles-Enhanced Magnetic Resonance Angiography

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

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

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

    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

    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

    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

    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

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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