Realizing 32-time Scan Duration Reduction of 18F-FDG PET Using Deep Learning Model with Image Augmentation

Realizing 32-time Scan Duration Reduction of 18F-FDG PET Using Deep Learning Model with Image Augmentation

Purpose: 32-time scan duration reduction of 18F-FDG Positron Emission Tomography (PET) images through the generation of standard scan duration images using a multi-slice cycle-consistent Generative Adversarial Network (cycle-GAN) was studied. Also, the effect of the image augmentation methods on th...

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Bibliographic Details
Main Authors: Ali Ghafari, Peyman Sheikhzadeh, Negisa Seyyedi, Mehrshad Abbasi, Mohammad Reza Ay
Format: Article
Language:English
Published: Tehran University of Medical Sciences 2022-08-01
Series:Frontiers in Biomedical Technologies
Subjects:
Image Augmentation
18F-Fluorodeoxyglucose
Positron Emission Tomography
Deep Learning
Online Access:https://fbt.tums.ac.ir/index.php/fbt/article/view/495

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https://fbt.tums.ac.ir/index.php/fbt/article/view/495

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