DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hyun, Subong | ko |
dc.contributor.author | Lee, Seoyoung | ko |
dc.contributor.author | Jeong, Uijin | ko |
dc.contributor.author | Cho, Seungryong | ko |
dc.date.accessioned | 2024-06-20T10:00:42Z | - |
dc.date.available | 2024-06-20T10:00:42Z | - |
dc.date.created | 2024-06-20 | - |
dc.date.created | 2024-06-20 | - |
dc.date.issued | 2024-06-11 | - |
dc.identifier.citation | 17th International Workshop on Breast Imaging (IWBI 2024) | - |
dc.identifier.uri | http://hdl.handle.net/10203/319903 | - |
dc.publisher | SPIE | - |
dc.title | Asymmetric scatter kernel superposition-inspired deep learning approach to estimate scatter in breast tomosynthesis | - |
dc.type | Conference | - |
dc.type.rims | CONF | - |
dc.citation.publicationname | 17th International Workshop on Breast Imaging (IWBI 2024) | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | Chicago, United States | - |
dc.identifier.doi | 10.1117/12.3024774 | - |
dc.contributor.localauthor | Cho, Seungryong | - |
dc.contributor.nonIdAuthor | Jeong, Uijin | - |
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