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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...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2016
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| Materias: | |
| 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 |