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/debate

19 Scopus citations

Abstract

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
Volume50
Issue number4
DOIs
StatePublished - Dec 2019

Keywords

  • 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

Fingerprint Dive into the research topics of 'Machine Learning and Deep Learning in Medical Imaging: Intelligent Imaging'. Together they form a unique fingerprint.

Cite this