Dynamic PET Image Denoising With Deep Learning-Based Joint Filtering

Dynamic PET Image Denoising With Deep Learning-Based Joint Filtering

Dynamic positron emission tomography (PET) imaging usually suffers from high statistical noise due to low counts of the short frames. This study aims to improve the image quality of the short frames by utilizing information from other modality. We develop a deep learning-based joint filtering framew...

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Bibliographic Details
Main Authors: Yuru He, Shuangliang Cao, Hongyan Zhang, Hao Sun, Fanghu Wang, Huobiao Zhu, Wenbing Lv, Lijun Lu
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Positron emission tomography
convolution neural network
denoising
spatially variant linear representation model
joint filtering
Online Access:https://ieeexplore.ieee.org/document/9373391/

Internet

https://ieeexplore.ieee.org/document/9373391/

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