Assessment of automatic rib fracture detection on chest CT using a deep learning algorithm.
| Publicado en: | European Radiology Vol. 33; no. 3; pp. 1824 - 1835 |
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| Autores principales: | , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Mar2023
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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=161963574&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 161963574 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: Mar2023 vid: 33 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 161963574 159574500 10.1007/s00330-022-09156-w 161963574 ppf: 1824 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Assessment of automatic rib fracture detection on chest CT using a deep learning algorithm. aug: au: Wang, Shuhao Wu, Dijia Ye, Lifang Chen, Zirong Zhan, Yiqiang Li, Yuehua affil: Department of Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No. 600, Yi Shan Road, 200233, Shanghai, China sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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