Modern machinery learning techniques allow for the processing of large quantities of cancer images, at a much faster rate than could be done manually. However, as Julia Schnabel, PhD, of Kings College London, London, UK, explains here, to unlock this potential there is the problem of manually producing a large enough database for the modern machinery to learn and process new data from. This interview was recorded at the 2017 National Cancer Research Institute (NCRI) Conference, held in Liverpool, UK.
The chicken and the egg: processing cancer imaging data so that more can be processed
