School of Electrical Engineering and Computer Science

Research and objectives

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Research

Our Biomedical Imaging & Sensing Group at the University of Queensland conducts research in MR method development for applications in neuroimaging, particularly in functional MRI (fMRI) and neurological diseases such as dementia, cancer, and cardiac MR. The group offers a unique combination of expertise in MRI acquisition, image processing and clinical applications. 

Objectives

The Biomedical Imaging & Sensing Research Group’s objective is to investigate the development of MR methods and technologies that can be translated into real-world applications in the health sector. The Group works with industry and clinical partners to identify most relevant needs and problems, design solutions and translate developed concepts into production.

Research focus

Magnetic Resonance (MRI) is a versatile technique that can provide important insights into the body non-invasively and without dangerous side effects with high spatial resolution. Professor Markus Barth is a leader in the fields of MR method development for applications in neuroimaging with a focus on functional MRI and neurological diseases such as dementia and cancer, as well as cardiac MR.

  • Understanding brain activity using functional MRI: blood oxygenation level dependent (BOLD) functional MRI gives a good picture of neural activation and connectivity in the living human brain non-invasively. A/Prof Barth is particularly interested to identify small functional units of the brain, such as cortical layers and columns, in order to better understand brain function by developing very fast functional MRI techniques with the highest spatial resolution possible. Recently, he also addressed important neuroscientific questions such as memory consolidation during sleep and decoding measured functional signals (brain reading). He explored the possibilities of simultaneous acquisition of EEG and fMRI to examine the link between electrophysiology and BOLD task activity and large scale brain networks.

  • Ageing and dementia using MR Neuroimaging: Using high magnetic fields (3 and 7 Tesla) spatial resolution of images can be improved significantly. For example, very small venous vessels and small bleedings in the brain can be visualised using specific contrasts, namely susceptibility weighted imaging (SWI) and MR phase. The MR phase information can be used as a very sensitive disease marker, e.g. for tumor angiogenesis or iron accumulation in certain brain structures in Parkinson’s disease.

  • Cardiac MR: A new area of research is the exploration of cardiac MR at the ultra-high field strength of 7 Tesla and first results examining the anatomy and function of the human heart look promising.

Medical Imaging provides unique insights into disease processes and enables improved therapies for a large range of patients.

The imaging process and the interpretation of data can be very complex and extends from basic science to engineering implementations to business needs. The computational imaging group of Dr Steffen Bollmann develops algorithms that enable clinicians and researchers to analyse complex multidimensional medical imaging data.

Research themes:

  • Image processing 
  • Computational tools development to extract information from rich medical imaging datasets, such as Quantitative Susceptibility Mapping (QSM).
  • NeuroDesk: Translation of image processing algorithms is driven by the development of the open-source Neurodesk software platform (www.neurodesk.org), which brings Neuroimaging and AI tools to end-users in a browser-based and barrier-free fashion. Neurodesk enables accessible, secure, and scalable image processing for medical imaging.

NeuroDesk – A cross-platform, flexible, lightweight, scalable, out-of-the-box analysis environment

We develop medical imaging methods for clinical applications, specialising in innovating magnetic resonance imaging (MRI) mechanisms. Led by Dr Hongfu Sun, the research team is particularly interested in developing deep learning methods to reconstruct and analyse images, as well as to improve disease diagnosis.

Current Projects
  • Fast, multi-parametric, and quantitative MRI acquisition methods at ultra-high field 
  • MR image processing through deep learning 
  • Brain imaging applications in neuroscience and neurological diseases 
 
Available HDR Topics

MRI and deep learning methods development and applications at ultra-high field 

Dr Hongfu Sun is currently recruiting PhD students to innovate on novel MRI methods and deep learning image reconstruction techniques that can be eventually applied to neuroscience and neurological diseases. We have an excellent and accessible MRI facility here at UQ, e.g. a state-of-the-art 3T Prisma and a prestigious 7T whole-body system (only two in Australia, the other one being at the University of Melbourne).

The research projects will involve MRI physics, pulse sequence programming, image processing (e.g. deep learning), and image analysis.

By the end of your graduate study, you will be an expert in MRI with comprehensive skills in maths, physics, computer programming, and artificial intelligence.