Improving PET Imaging Acquisition and Analysis With Machine Learning: A Narrative Review With Focus on Alzheimer's Disease and Oncology
Machine learning (ML) algorithms have found increasing utility in the medical imaging field and numerous applications in the analysis of digital biomarkers within positron emission tomography (PET) imaging have emerged. Interest in the use of artificial intelligence in PET imaging for the study of n...
Main Authors: | Ian R. Duffy PhD, Amanda J. Boyle PhD, Neil Vasdev PhD |
---|---|
Format: | Article |
Language: | English |
Published: |
SAGE Publishing
2019-08-01
|
Series: | Molecular Imaging |
Online Access: | https://doi.org/10.1177/1536012119869070 |
Similar Items
-
Emerging PET Radiotracers and Targets for Imaging of Neuroinflammation in Neurodegenerative Diseases: Outlook Beyond TSPO
by: Vidya Narayanaswami PhD, et al.
Published: (2018-09-01) -
Preclinical PET Neuroimaging of [C]Bexarotene
by: Benjamin H. Rotstein PhD, et al.
Published: (2016-08-01) -
Brain Penetration of the ROS1/ALK Inhibitor Lorlatinib Confirmed by PET
by: T. Lee Collier PhD, et al.
Published: (2017-10-01) -
Detecting Demyelination by PET: The Lesion as Imaging Target
by: Pedro Brugarolas PhD, et al.
Published: (2018-07-01) -
The Search for a Subtype-Selective PET Imaging Agent for the GABA Receptor Complex: Evaluation of the Radiotracer [C]ADO in Nonhuman Primates
by: Shu-fei Lin PhD, et al.
Published: (2017-09-01)