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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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Библиографические подробности
Опубликовано в: :Sci Rep
Главные авторы: Fu, Zhiyang, Tseng, Hsin Wu, Vedantham, Srinivasan, Karellas, Andrew, Bilgin, Ali
Формат: Artigo
Язык:Inglês
Опубликовано: Nature Publishing Group UK 2020
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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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