Intelligent imaging: Anatomy of machine learning and deep learning

Research output: Contribution to journalArticlepeer-review

34 Citations (Scopus)


The emergence of artificial intelligence (AI) in nuclear medicine and radiology has been accompanied by AI commentators and experts predicting that AI would make radiologists, in particular, extinct. More realistic perspectives suggest significant changes will occur in medical practice. There is no escaping the disruptive technology associated with AI, neural networks, and deep learning, the most significant perhaps since the early days of Roentgen, Becquerel, and Curie. AI is an omen, but it need not be foreshadowing a negative event; rather, it is heralding great opportunity. The key to sustainability lies not in resisting AI but in having a deep understanding and exploiting the capabilities of AI in nuclear medicine while mastering those capabilities unique to the human resources.
Original languageEnglish
Pages (from-to)273-281
Number of pages9
JournalJournal of Nuclear Medicine Technology
Issue number4
Publication statusPublished - 01 Dec 2019


Dive into the research topics of 'Intelligent imaging: Anatomy of machine learning and deep learning'. Together they form a unique fingerprint.

Cite this