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Review ArticleContinuing Education

Machine Learning in Nuclear Medicine: Part 2—Neural Networks and Clinical Aspects

Katherine Zukotynski, Vincent Gaudet, Carlos F. Uribe, Sulantha Mathotaarachchi, Kenneth C. Smith, Pedro Rosa-Neto, François Bénard and Sandra E. Black
Journal of Nuclear Medicine January 2021, 62 (1) 22-29; DOI: https://doi.org/10.2967/jnumed.119.231837
Katherine Zukotynski
1Departments of Medicine and Radiology, McMaster University, Hamilton, Ontario, Canada
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Vincent Gaudet
2Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario, Canada
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Carlos F. Uribe
3PET Functional Imaging, BC Cancer, Vancouver, British Columbia, Canada
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Sulantha Mathotaarachchi
4Translational Neuroimaging Lab, McGill University, Montreal, Quebec, Canada
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Kenneth C. Smith
5Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada
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Pedro Rosa-Neto
4Translational Neuroimaging Lab, McGill University, Montreal, Quebec, Canada
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François Bénard
3PET Functional Imaging, BC Cancer, Vancouver, British Columbia, Canada
6Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada; and
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Sandra E. Black
7Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
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Article Information

vol. 62 no. 1 22-29
DOI 
https://doi.org/10.2967/jnumed.119.231837
PubMed 
32978286

Published By 
Society of Nuclear Medicine
Print ISSN 
0161-5505
Online ISSN 
2159-662X
History 
  • Received for publication April 26, 2020
  • Accepted for publication August 13, 2020
  • Published online December 17, 2020.

Article Versions

  • previous version (September 25, 2020 - 15:05).
  • You are viewing the most recent version of this article.
Copyright & Usage 
© 2021 by the Society of Nuclear Medicine and Molecular Imaging.

Author Information

  1. Katherine Zukotynski*,1,
  2. Vincent Gaudet*,2,
  3. Carlos F. Uribe3,
  4. Sulantha Mathotaarachchi4,
  5. Kenneth C. Smith5,
  6. Pedro Rosa-Neto4,
  7. François Bénard3,6 and
  8. Sandra E. Black7
  1. 1Departments of Medicine and Radiology, McMaster University, Hamilton, Ontario, Canada
  2. 2Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario, Canada
  3. 3PET Functional Imaging, BC Cancer, Vancouver, British Columbia, Canada
  4. 4Translational Neuroimaging Lab, McGill University, Montreal, Quebec, Canada
  5. 5Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada
  6. 6Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada; and
  7. 7Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
  1. For correspondence or reprints contact: Katherine Zukotynski, Departments of Medicine and Radiology, McMaster University, 1200 Main St. W., Room 1P11, Hamilton, ON L8N 3Z5, Canada. E-mail: katherine.zukotynski{at}utoronto.ca
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Journal of Nuclear Medicine: 62 (1)
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Machine Learning in Nuclear Medicine: Part 2—Neural Networks and Clinical Aspects
Katherine Zukotynski, Vincent Gaudet, Carlos F. Uribe, Sulantha Mathotaarachchi, Kenneth C. Smith, Pedro Rosa-Neto, François Bénard, Sandra E. Black
Journal of Nuclear Medicine Jan 2021, 62 (1) 22-29; DOI: 10.2967/jnumed.119.231837

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Machine Learning in Nuclear Medicine: Part 2—Neural Networks and Clinical Aspects
Katherine Zukotynski, Vincent Gaudet, Carlos F. Uribe, Sulantha Mathotaarachchi, Kenneth C. Smith, Pedro Rosa-Neto, François Bénard, Sandra E. Black
Journal of Nuclear Medicine Jan 2021, 62 (1) 22-29; DOI: 10.2967/jnumed.119.231837
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  • Article
    • Abstract
    • BRIEF REVIEW FROM PART 1
    • ANNS: UNDERSTANDING BY EXAMPLE
    • NEURAL NETWORKS IN NUCLEAR MEDICINE: A SPECTRUM OF APPLICATIONS
    • CONCLUSION
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Keywords

  • machine learning
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