Artificial intelligence and medical imaging: applications, challenges and solutions

Meng Law, Jarrel Seah and George Shih
Med J Aust 2021; 214 (10): . || doi: 10.5694/mja2.51077
Published online: 7 June 2021

AI‐based tools can help with image acquisition, reconstruction and quality; interpretation, diagnosis and decision support; and manual tasks

Artificial intelligence (AI) is having a disruptive impact in many areas, including health care. In medicine, machine learning (ML) techniques have existed for decades but were mostly not adopted. New deep learning techniques, along with copious medical imaging and digital health data, now provide standardised, reproducible, dependable and accurate diagnostic reports. These can only improve patient care and safety, enhancing the practice of clinical medicine. However, a number of challenges have arisen, hindering progress and more widespread application. In this article, we describe current AI/ML tools in medical imaging, discuss the major challenges facing the field, and offer some potential solutions.

  • Meng Law1,2
  • Jarrel Seah3
  • George Shih4

  • 1 Alfred Health, Melbourne, VIC
  • 2 Monash University, Melbourne, VIC
  • 3 Alfred Hospital, Melbourne, VIC
  • 4 Weill Cornell Medicine, New York, NY, USA


Competing interests:

No relevant disclosures.


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