I provide a full range of image analysis support in Clinical Research Studies, from general image processing tasks to custom software development.  My major areas of research have focussed on:

• Development of non-invasive imaging-based biomarkers of disease (encompassing cardiovascular disease, diabetes, fetal imaging, novel MRI contrast agents, and quantitative assessment of muscle and adipose tissue)
• Development of new/novel post-processing and analysis techniques on data from medical imaging modalities - including MRI, CT, PET, ultrasound, microscopy, and photography (conventional and retinal)
• Application of image processing, manipulation and quantification techniques (e.g. registration, segmentation, region of interest analysis, volumetric analysis, image enhancement, and 3D visualisation)

Why is it important?
Non-invasive imaging techniques are essential diagnostic tools in modern medicine, allowing the study of disease or the effect of a drug in vivo, over a period of time.  In clinical research, non-invasive imaging can assist in the discovery and assessment of biomarkers (a measureable characteristic or indicator reflecting the severity or presence of a disease state).  Biomarkers will aid the path to personalised medicine, where treatments are individually tailored to specific patients to allow highly efficient intervention in disease processes.  However, modern non-invasive imaging modalities such as computerised tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and ultrasound can yield huge volumes of data, and therefore require sophisticated data/image processing techniques to handle and make sense of all the information.