AI could be our radiologists of the future, amid a healthcare staff crisis

Research output: Contribution to specialist publicationArticle


It is almost 40 years since a full-body magnetic resonance imaging machine was used for the first time to scan a patient and generate diagnostic-quality images. The scanner and signal processing methods needed to produce an image were devised by a team of medical physicists including John Mallard, Jim Hutchinson, Bill Edelstein and Tom Redpath at the University of Aberdeen, leading to widespread use of the MRI scanner, now a ubiquitous tool in radiology departments across the world.

MRI was a game changer in medical diagnostics because it didn’t require exposure to ionising radiation (such as X-rays), and could generate images on multiple cross-sections of the body with superb definition of soft tissues. This allowed, for example, the direct visualisation of the spinal cord for the first time.
Original languageEnglish
Specialist publicationThe Conversation
Publication statusPublished - 8 Aug 2019

Bibliographical note

Alison Murray receives funding from Innovate UK, the European Commission, the Wellcome Trust, the Chief Scientist Office, the Scottish Funding Council (via the Scottish Imaging Network: A Platform of Scientific Excellence) and the University of Aberdeen.


  • Artificial intelligence (AI)
  • MRI
  • Healthcare
  • Pathology
  • NHS
  • Medical technology
  • Nuclear medicine
  • Cancer screening
  • NHS data
  • Data privacy
  • Radiology
  • Magnetic resonance imaging


Dive into the research topics of 'AI could be our radiologists of the future, amid a healthcare staff crisis'. Together they form a unique fingerprint.

Cite this