Biomedical imaging
Our research includes the development of techniques for image acquisition and analysis, with application to the understanding of biological structure and function.
Biomedical imaging encompasses a broad range of imaging expertise. We improve acquisition and reconstruction technologies, including:
- Ultra-high field Magnetic Resonance Imaging (MRI)
- Positron Emission Tomography (PET)
- Transcranial Magnetic Stimulation (TMS)
- Functional Near Infrared Spectroscopy (fNIRS).
We develop imaging analysis tools with specialties in microCT and microscopy methods for mechanobiology research, and MRI-based connectomics for the diagnosis and treatment of brain diseases and disorders.
We apply preclinical and clinical imaging modalities to a range of biomedical engineering fields including musculoskeletal, neurological and mechanobiological research.
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Cell Systems and Mechanobiology Lab
We uncover the inner workings of living cells by creating in-silico models of cell structure, its mechanics and biochemical processes that drive cell function. Our research has led to fundamental discoveries related to heart disease, cancer and blood and vascular diseases.
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Integrative Cartilage Research Group
Applying innovative technologies in order to reveal the mechanobiological signalling networks in cartilage and joint disorders and provide strategies for repair.
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Melbourne Brain Centre Imaging Unit
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Systems Lab
We use neuroimaging techniques to conduct research into the human brain in health and mental illness. We develop advanced computational models and tools to study brain networks and systems, and apply the knowledge gained from these studies to develop improved brain stimulation and other therapies.
The following list represents a selection of projects belonging to our researchers.
— indicates projects currently recruiting research students. Visit our Study website for PhD program and application information.
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Data and image analysis of arthritis progression
Team: Kathryn Stok, Catherine Davey
Digital image processing of arthritis progression
Team: Kathryn Stok
Time-lapsed imaging of arthritis progression
Team: Kathryn Stok, Catherine Davey
Efficient and effective adaptive radiotherapy
Team: Leigh Johnston
Use of Deep Learning computational methods to characterise cancer burden in PET imaging
Team: Leigh Johnston
Radiomics for cancer diagnosis and patient outcome prediction
Team: Leigh Johnston