Case study: Vaanathi Sundaresan
As an Engineering Masters student at the Indian Institute of Technology Madras, India, Vaanathi worked on image analysis projects relating to diabetic retinopathy and age-related macular degeneration. Having become interested in using these methods to help in managing serious illness, Vaanathi wished to continue her research at a doctoral level on biomedical image processing and analysis methods such as registration, segmentation and modelling, which would assist in deriving clinically useful information from medical images.
Vaanathi’s chosen project focuses on detecting structural anomalies occurring in brain white matter, thus assisting in the diagnosis and management of various neurodegenerative diseases. The ultimate aim of her research is to create a single automated tool using multiple MRI image modalities to exploit different characteristics (intensity, shape and dimension) of white matter hyperintensities, cerebral microbleeds, lacunar infarcts and perivascular spaces, and to make the analysis robust across large, wide-ranging imaging databases such as the UK Biobank. This is highly novel research that would fulfil an unmet need in the field.
Arising from her preliminary work, Vaanathi has already been a co-author on a paper published in the prestigious international journal NeuroImage