Image-spectral decomposition extended-learning assisted by sparsity for multi-energy computed tomography reconstruction

BACKGROUND: Multi-energy computed tomography (CT) provides multiple channel-wise reconstructed images, and they can be used for material identification and k-edge imaging. Nonetheless, the projection datasets are frequently corrupted by various noises (e.g., electronic, Poisson) in the acquisition p...

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Detalles Bibliográficos
Autores principales: Wang, Shaoyu, Wu, Weiwen, Cai, Ailong, Xu, Yongshun, Vardhanabhuti, Varut, Liu, Fenglin, Yu, Hengyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9929415/
https://www.ncbi.nlm.nih.gov/pubmed/36819292
http://dx.doi.org/10.21037/qims-22-235

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9929415/
https://www.ncbi.nlm.nih.gov/pubmed/36819292
http://dx.doi.org/10.21037/qims-22-235

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