Low-dose CT reconstruction via L1 dictionary learning regularization using iteratively reweighted least-squares

BACKGROUND: In order to reduce the radiation dose of CT (computed tomography), compressed sensing theory has been a hot topic since it provides the possibility of a high quality recovery from the sparse sampling data. Recently, the algorithm based on DL (dictionary learning) was developed to deal wi...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Cheng, Zhang, Tao, Li, Ming, Peng, Chengtao, Liu, Zhaobang, Zheng, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4912768/
https://www.ncbi.nlm.nih.gov/pubmed/27316680
http://dx.doi.org/10.1186/s12938-016-0193-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4912768/
https://www.ncbi.nlm.nih.gov/pubmed/27316680
http://dx.doi.org/10.1186/s12938-016-0193-y

Ejemplares similares