Approximating anatomically-guided PET reconstruction in image space using a convolutional neural network

Approximating anatomically-guided PET reconstruction in image space using a convolutional neural network

In the last two decades, it has been shown that anatomically-guided PET reconstruction can lead to improved bias-noise characteristics in brain PET imaging. However, despite promising results in simulations and first studies, anatomically-guided PET reconstructions are not yet available for use in r...

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Bibliographic Details
Main Authors: Georg Schramm, David Rigie, Thomas Vahle, Ahmadreza Rezaei, Koen Van Laere, Timothy Shepherd, Johan Nuyts, Fernando Boada
Format: Article
Language:English
Published: Elsevier 2021-01-01
Series:NeuroImage
Subjects:
Molecular imaging
Magnetic resonance imaging
Image reconstruction
Quantification
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S1053811920308843

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http://www.sciencedirect.com/science/article/pii/S1053811920308843

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