AI-driven attenuation correction for brain PET/MRI: Clinical evaluation of a dementia cohort and importance of the training group size

AI-driven attenuation correction for brain PET/MRI: Clinical evaluation of a dementia cohort and importance of the training group size

Introduction: Robust and reliable attenuation correction (AC) is a prerequisite for accurate quantification of activity concentration. In combined PET/MRI, AC is challenged by the lack of bone signal in the MRI from which the AC maps has to be derived. Deep learning-based image-to-image translation...

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Bibliographic Details
Main Authors: Claes Nøhr Ladefoged, Adam Espe Hansen, Otto Mølby Henriksen, Frederik Jager Bruun, Live Eikenes, Silje Kjærnes Øen, Anna Karlberg, Liselotte Højgaard, Ian Law, Flemming Littrup Andersen
Format: Article
Language:English
Published: Elsevier 2020-11-01
Series:NeuroImage
Subjects:
Attenuation correction
Deep learning
Convolutional neural network
Artificial intelligence
Brain
PET/MRI
Online Access:http://www.sciencedirect.com/science/article/pii/S1053811920307072

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http://www.sciencedirect.com/science/article/pii/S1053811920307072

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