Medical image computing for next-generation healthcare technology

At the heart of this platform is a vision of the future of medical technology enabled by the increasing availability of rich and diverse data from large-scale data collection initiatives. The vision is to exploit this data mass to enrich sparse data acquired at point of care. For example, a single clinical MRI or ultrasound scan, together with subject-specific clinical data (age, sex, symptoms, genetics) can index a centralised data mass to infer likely diagnosis, prognosis, and treatment outcomes by matching to similar individuals about whom much more is known. The same paradigm further enables cheap and/or small and/or low-power devices able to acquire data in non-specialist locations, such as portable or hand-held scanners, or tiny imaging devices in surgical instruments.

Platform funding will maintain our world-leading activities in a range of medical image computing topics, support alignment of currently distinct strands of work for mutual short-term benefit, and develop key enabling technology and demonstrators of our long-term vision. Our current work develops state of the art imaging technology, image analysis techniques, and mathematical and computational models that maximise the information contained in and derived from large data sets. We also develop a range of automated diagnostic systems and surgical support systems that can demonstrate the benefits of the data-driven paradigm.

Platform funding supports the career development of the applicants, a pool of associated academic staff, talented post-doctoral researchers, and students coming through an associated EPSRC Centre for Doctoral Training in Medical Imaging. The platform provides opportunities for all to develop new ideas crossing boundaries between different topics, while contributing to a central long-term vision that supports a variety of future research careers. Competitive allocation of resource under close mentorship of senior colleagues instils early-career researchers with essential academic skills required for successful future careers. It further enhances the career progression of our senior staff by supporting opportunities to acquire new skills, establish new collaborations, explore commercialisation, and recruit the best staff from around the world when opportunities arise.

Medical image computing is a linchpin of modern medicine and biomedical research. It provides the mathematical and computational models and algorithms that link biomedical image data to an understanding of tissue-and-body structure and function in health and disease. This is the foundation for current and future drug/treatment discovery, development, and deployment.

Our work impacts most directly on neurological diseases and cancer. The UK dementia platform estimates annual socioeconomic costs of dementia in Britain at around £17B. A treatment prolonging independent life of dementia patients by just one year would save around £1B per year in care costs as well as boosting the UK economy through revenue from the treatment if realised through its pharmaceutical industry and thriving community of related SMEs. Annual costs of cancer have similar scale; our work in early diagnostics and treatment delivery offers similar socio-economic impact.

A key impact of our long-term vision of medical technology is to make accurate diagnostic and prognostic testing widely accessible in non-specialist scenarios. For example, measurements from a handheld scanner at a local doctor's surgery, pharmacy, or field hospital, coupled with clinical data link to a central information resource to obtain suggestions of diagnosis, prognosis, treatment assignment and/or further testing strategy. This reduces the cost of patient examinations, reduces the need for invasive tests, and decreases the delay in moving from assessment to treatment. Ultimately for the patient, this leads to cheaper, faster and more accurate diagnosis, more reliable prognosis, reduction of side effects from diagnostic tests, and better-targeted treatment and care. Economically, it stimulates industry to develop and market new drugs and devices for assessment and treatment. This in turn reduces the burden on the healthcare system by prolonging independent good-quality life.