Machine Learning and Deep Learning in Medical Imaging: Intelligent Imaging

Geoff Currie, K. Elizabeth Hawk, Eric Rohren, Alanna Vial, Ran Klein

Research output: Contribution to journalComment/debatepeer-review

247 Scopus citations


Artificial intelligence (AI) in medical imaging is a potentially disruptive technology. An understanding of the principles and application of radiomics, artificial neural networks, machine learning, and deep learning is an essential foundation to weave design solutions that accommodate ethical and regulatory requirements, and to craft AI-based algorithms that enhance outcomes, quality, and efficiency. Moreover, a more holistic perspective of applications, opportunities, and challenges from a programmatic perspective contributes to ethical and sustainable implementation of AI solutions.

Original languageEnglish (US)
Pages (from-to)477-487
Number of pages11
JournalJournal of Medical Imaging and Radiation Sciences
Issue number4
StatePublished - Dec 2019


  • Medical imaging
  • artificial intelligence
  • artificial neural network
  • convolutional neural network
  • deep learning

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging


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