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A residual dense network assisted sparse view reconstruction for breast computed tomography
To develop and investigate a deep learning approach that uses sparse-view acquisition in dedicated breast computed tomography for radiation dose reduction, we propose a framework that combines 3D sparse-view cone-beam acquisition with a multi-slice residual dense network (MS-RDN) reconstruction. Pro...
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| Опубликовано в: : | Sci Rep |
|---|---|
| Главные авторы: | , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Nature Publishing Group UK
2020
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7713379/ https://ncbi.nlm.nih.gov/pubmed/33273541 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-020-77923-0 |
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