From Rock-and-Roll to Sailing in the Rain via 47 Years of Fun in Medical Imaging

This talk provides a personal tour from the early days of CT and quantitative 3D imaging, through to the application of imaging with machine learning to guide interventions and understand disease progression. I will describe how early applications of quantitative CT led to tissue characterisation in cancer, why spatial alignment of images became important and how this led to the advent of image guided interventions. Recent work in improving minimally invasive liver surgery and the management of prostate cancer demonstrates how these technologies have developed. The importance of a multiscale approach, understanding the cellular structure of disease, is enabling advances in prostate cancer diagnosis. Work in image guided lung radiotherapy led to work in chronic obstructive lung disease (COPD). Application of novel machine learning techniques, originally developed to understand the progression of Alzheimer’s disease, enables the study of COPD progression. The COVID pandemic provided opportunities to apply these ideas to better understand the progression of severe infectious disease. I have learnt that bringing together groups working in many disease areas allows cross fertilisation of ideas and methods, and at the same time provides challenges requiring novel engineering solutions. Establishing close links between healthcare providers, industry and academia promotes translation of these new ideas to the clinic.