Machine Learning in Nuclear Medicine: Part 2—Neural Networks and Clinical Aspects Journal Articles uri icon

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  • This article is the second part in our machine learning series. Part 1 provided a general overview of machine learning in nuclear medicine. Part 2 focuses on neural networks. We start with an example illustrating how neural networks work and a discussion of potential applications. Recognizing that there is a spectrum of applications, we focus on recent publications in the areas of image reconstruction, low-dose PET, disease detection, and models used for diagnosis and outcome prediction. Finally, since the way machine learning algorithms are reported in the literature is extremely variable, we conclude with a call to arms regarding the need for standardized reporting of design and outcome metrics and we propose a basic checklist our community might follow going forward.


  • Zukotynski, Katherine
  • Gaudet, Vincent
  • Uribe, Carlos F
  • Mathotaarachchi, Sulantha
  • Smith, Kenneth C
  • Rosa-Neto, Pedro
  • Bénard, François
  • Black, Sandra E

publication date

  • January 2021