Dual-Domain deep prior guided sparse-view CT reconstruction with multi-scale fusion attention

Dual-Domain deep prior guided sparse-view CT reconstruction with multi-scale fusion attention

Abstract Sparse-view CT reconstruction is a challenging ill-posed inverse problem, where insufficient projection data leads to degraded image quality with increased noise and artifacts. Recent deep learning approaches have shown promising results in CT reconstruction. However, existing methods often...

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Bibliographic Details
Main Authors: Jia Wu, Jinzhao Lin, Xiaoming Jiang, Wei Zheng, Lisha Zhong, Yu Pang, Hongying Meng, Zhangyong Li
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Sparse-view CT reconstruction
Deep prior
Multi-scale fusion attention
Model-based optimization
Physics-informed consistency
Online Access:https://doi.org/10.1038/s41598-025-02133-5
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https://doi.org/10.1038/s41598-025-02133-5

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