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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...
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| Опубликовано в: : | Biomed Eng Online |
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| Главные авторы: | , , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
BioMed Central
2016
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4912768/ https://ncbi.nlm.nih.gov/pubmed/27316680 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12938-016-0193-y |
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