Dr Xiaoyun Liang
Areas of expertise: Magnetic Resonance Imaging, Neuroimaging, Machine learning, Data analytics
ORCID ID: 0000-0002-1851-3408
Location: ACU Melbourne Campus
Dr. Liang is a MR physicist with PhD degree in Biomedical Engineering. He has been mainly working on developing neuroimaging techniques using magnetic resonance imaging. In particular, he has developed novel techniques in mapping human brain connectomes, including both functional and structural connectomes, as well as the development of approaches for graph theoretical analysis of complex networks. Meanwhile, he has expertise in machine learning and deep learning, which has been shown to offer new insights into defining neuroimaging biomarkers given the current trend of collecting large cohorts through international collaborations. Importantly, those developed techniques have been applied to patients with various brain disorders, such as stroke, epilepsy, Alzheimer’s disease and dementia, of which some have been translated into clinical practice. He has published over 30 peer-reviewed journal articles in high-impact journals, such as NeuroImage, Human Brain Mapping, Magnetic Resonance in Medicine, Brain Structure and Function, etc. Also, Dr. Liang has been actively involved in peer-review process, which he has reviewed more than 60 manuscripts for more than 10 top journals, such as NeuroImage, Neurology, Journal of Magnetic Resonance Imaging, IEEE Transactions on Biomedical Engineering, Physics in Medicine and Biology, Brain Topography, etc. He currently serves as an Associate Editor of Journal of Magnetic Resonance Imaging, one of the two official Journals of International Society of Magnetic Resonance in Medicine.
- Amir Fazlollahi, Fernando Calamante, Xiaoyun Liang, Pierrick Bourgeat, et al. Increased Cerebral Blood Flow with Increased Amyloid burden in the preclinical phase of Alzheimer’s disease. Journal of Magnetic Resonance Imaging (In press).
- Xiaoyun Liang*, Chun-Hung Yeh, Alan Connelly, Fernando Calamante. A novel method for extracting hierarchical functional subnetworks based on a multi-subject spectral clustering approach. Brain Connectivity 9(5):399-414.
- Jiantao Zhu, Ningfan Hu, Xiaoyun Liang, Xiaojing Li, Jian Guan, Yajuan Wang, Ligong Wang. T2 mapping of cartilage and menisci at 3T in healthy subjects with knee malalignment: initial experience. Skeletal Radiology 48(5):753-763.
- Xiaoyun Liang*, Chun-Hung Yeh, Alan Connelly, Fernando Calamante. Robust identification of rich-club organization in weighted and dense structural connectomes. Brain Topography 32(1): 1-16.
- Xiaoyun Liang*, David Vaughan, Alan Connelly, Fernando Calamante (2018). A novel group-fused sparse partial correlation method for simultaneous estimation of functional networks in group comparison studies. Brain Topography 31(3): 364-379.
- Fernando Calamante, Robert Smith, Xiaoyun Liang, Andrew Zalesky, Alan Connelly (2017). Track-weighted dynamic functional connectivity (TW-dFC): a new method to study time-resolved functional connectivity. Brain Structure and Function 222(8): 3761-3774.
- Chun-Hung Yeh, Robert Smith, Xiaoyun Liang, Fernando Calamante, Alan Connelly (2016). Correction for diffusion MRI fibre tracking biases: The consequences for structural connectomic metrics. NeuroImage 142: 150-162.
- Xiaoyun Liang*, Alan Connelly, Fernando Calamante (2016). A novel joint sparse partial correlation method for estimating group functional networks. Human Brain Mapping 37(3): 1162-1177.
- Amir Fazlollahi, Pierrick Bourgeat, Xiaoyun Liang, Fabrice Meriaudeau, Alan Connelly, Olivier Salvado, Fernando Calamante (2015). Reproducibility of multiphase pseudo-continuous arterial spin labeling and the effect of post-processing analysis methods. NeuroImage 117: 191-201.
- Xiaoyun Liang*, Alan Connelly, Fernando Calamante (2015). Voxel-wise functional connectomics using arterial spin labeling fMRI: the role of denoising. Brain Connectivity 5(9): 543-553.
- Xiaoyun Liang*, Alan Connelly, Donald Tournier, Fernando Calamante (2014). A variable flip angle-based method for reducing blurring in 3D GRASE ASL. Physics in Medicine and Biology 59: 5559-5573.
- Xiaoyun Liang*, Alan Connelly, Fernando Calamante (2014). Graph analysis of resting-state ASL perfusion MRI data: Nonlinear correlations among CBF and network metrics. NeuroImage 87: 265-275.
- Xiaoyun Liang*, Alan Connelly, Fernando Calamante (2013). Improved partial volume correction for single inversion time arterial spin labeling data. Magnetic Resonance in Medicine 69: 531-537
- Xiaoyun Liang*, Donald Tournier, Richard Masterton, Alan Connelly, Fernando Calamante (2012). A k-space sharing 3D GRASE pseudo-continuous ASL method for whole-brain resting-state functional connectivity. International Journal of Imaging Systems and Technology 22(1): 37-43 .
- Xiaoyun Liang, Leslie Zebrowitz, Yi Zhang (2010). Neural Activation in the ‘Reward- Circuit’ Shows a Nonlinear Response to Facial Attractiveness. Social Neuroscience 5(3): 320-34.
Accolades and awards
- Best Reviewer Award, Journal of Magnetic Resonance Imaging, 2018-2019
- Distinguished Reviewer Award, Journal of Magnetic Resonance Imaging, 2017-2018
- Distinguished Reviewer Award, Journal of Magnetic Resonance Imaging, 2016-2017
- Special Distinction Award, Journal of Magnetic Resonance Imaging, 2015-2016
- Distinguished Reviewer Award, Journal of Magnetic Resonance Imaging, 2013-2014
Appointments and affiliations
- Mary Mackillop Institute for Health Research, Australian Catholic University, Research Fellow, 01/2019~now;
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Senior Research Officer, 02/2010~now.
- Vanderbilt University, Institute of Imaging Science, Postdoctoral Research Fellow, EEG-fMRI in epilepsy patients, 08/2008~12/2009
- Associate Editor of Journal of Magnetic Resonance Imaging (JCR Q1) 12/2016~
International jorunal review panel
- NeuroImage, Neurology, Physics in Medicine and Biology, IEEE Transaction on Biomedical Engineering, Journal of Magnetic Resonance Imaging, Brain Topography, PLOS ONE, Frontiers in Neuroscience, Journal of Neuroradiology, Computational and Mathematical Methods in Medicine