RT Journal Article
SR Electronic
T1 Machine Learning in Nuclear Medicine: Part 2—Neural Networks and Clinical Aspects
JF Journal of Nuclear Medicine
JO J Nucl Med
FD Society of Nuclear Medicine
SP 22
OP 29
DO 10.2967/jnumed.119.231837
VO 62
IS 1
A1 Zukotynski, Katherine
A1 Gaudet, Vincent
A1 Uribe, Carlos F.
A1 Mathotaarachchi, Sulantha
A1 Smith, Kenneth C.
A1 Rosa-Neto, Pedro
A1 Bénard, François
A1 Black, Sandra E.
YR 2021
UL http://jnm.snmjournals.org/content/62/1/22.abstract
AB 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.