Metal artifact reduction in computed tomography images based on developed generative adversarial neural network

Metal artifact reduction in computed tomography images based on developed generative adversarial neural network

Objectives: Metal artifacts are one of the major issues encountered in computed tomography (CT) images since they may make distinguishing healthy and tumor organs and computing dose distribution through radiotherapy very difficult. Accordingly, designing generative adversarial neural networks (GANs)...

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Bibliographic Details
Main Authors: Goli Khaleghi, Mohammad Hosntalab, Mahdi Sadeghi, Reza Reiazi, Seied Rabi Mahdavi
Format: Article
Language:English
Published: Elsevier 2021-01-01
Series:Informatics in Medicine Unlocked
Subjects:
Metal artifacts
GAN
Neural networks
Denoising
Online Access:http://www.sciencedirect.com/science/article/pii/S2352914821000630

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