Detection of intracranial aneurysms using deep learning-based CAD system: usefulness of the scores of CNN's final layer for distinguishing between aneurysm and infundibular dilatation.
| Publicado en: | Japanese Journal of Radiology Vol. 41; no. 2; pp. 131 - 142 |
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| Autores principales: | , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Feb2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=161607295&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 161607295 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 18671071 AUCM jtl: Japanese Journal of Radiology issn: 18671071 maglogo: N pubinfo: dt: Feb2023 vid: 41 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 161607295 159395712 10.1007/s11604-022-01341-7 161607295 ppf: 131 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Detection of intracranial aneurysms using deep learning-based CAD system: usefulness of the scores of CNN's final layer for distinguishing between aneurysm and infundibular dilatation. aug: au: Ishihara, Makiko Shiiba, Masato Maruno, Hirotaka Kato, Masayuki Ohmoto-Sekine, Yuki Antoine, Choppin Ouchi, Yasuyoshi affil: Department of Diagnostic Imaging Center, Toranomon Hospital, 1-8-1 Akasaka Intercity AIR 5F, Akasaka, Minato-ku, 107-0052, Tokyo, Japan sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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