Biomedical Image Analysis
The Biomedical Image Analysis Laboratory has a strong tradition of developing image analysis techniques that show potential for high impact in clinical practice and are taken from first feasibility studies all the way through to clinical translation and commercial exploitation with clinical and industrial partners.
Its interests cover a diverse range of established clinical imaging modalities (ultrasound, MRI, PET, CT), emerging clinical imaging modalities (elastography, EMA, dynamic PET, hyperpolarised MRI), and where appropriate their combination thereof, for structural, functional and metabolic analysis, as well as biological image analysis. Underpinning much of the research is the need to develop new methodologies that can extract the useful information from very large datasets. Developed methodologies advance the use of imaging and image analysis in cardiology, oncology, women’s health (obstetrics and perinatal care) and microscopy.
Examples of recent research which show high promise for clinical translation include work on machine learning applied in ultrasound and microscopy imaging (Noble), magnetic resonance imaging of lung function using hyperpolarised gases (Grau) and quantitative metabolic imaging for personalized stroke treatment planning (Chappell).