Mud-Net: multi-domain deep unrolling network for simultaneous sparse-view and metal artifact reduction in computed tomography

Mud-Net: multi-domain deep unrolling network for simultaneous sparse-view and metal artifact reduction in computed tomography

Sparse-view computed tomography (SVCT) is regarded as a promising technique to accelerate data acquisition and reduce radiation dose. However, in the presence of metallic implants, SVCT inevitably makes the reconstructed CT images suffer from severe metal artifacts and streaking artifacts due to the...

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Bibliographic Details
Main Authors: Baoshun Shi, Ke Jiang, Shaolei Zhang, Qiusheng Lian, Yanwei Qin, Yunsong Zhao
Format: Article
Language:English
Published: IOP Publishing 2024-01-01
Series:Machine Learning: Science and Technology
Subjects:
computed tomography
metal artifact reduction
sparse-view
multi-domain network
deep unrolling network
Online Access:https://doi.org/10.1088/2632-2153/ad1b8e

Internet

https://doi.org/10.1088/2632-2153/ad1b8e

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