DeepPVC: prediction of a partial volume-corrected map for brain positron emission tomography studies via a deep convolutional neural network

DeepPVC: prediction of a partial volume-corrected map for brain positron emission tomography studies via a deep convolutional neural network

Abstract Background Partial volume correction with anatomical magnetic resonance (MR) images (MR-PVC) is useful for accurately quantifying tracer uptake on brain positron emission tomography (PET) images. However, MR segmentation processes for MR-PVC are time-consuming and prevent the widespread cli...

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Bibliographic Details
Main Authors: Keisuke Matsubara, Masanobu Ibaraki, Toshibumi Kinoshita, for the Alzheimer’s Disease Neuroimaging Initiative
Format: Article
Language:English
Published: SpringerOpen 2022-07-01
Series:EJNMMI Physics
Subjects:
Deep learning
Partial volume correction
PET
Amyloid
Online Access:https://doi.org/10.1186/s40658-022-00478-8

Internet

https://doi.org/10.1186/s40658-022-00478-8

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