SSDL—an automated semi-supervised deep learning approach for patient-specific 3D reconstruction of proximal femur from QCT images.
| Publicado en: | Medical & Biological Engineering & Computing Vol. 62; no. 5; pp. 1409 - 1426 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
May2024
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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=176627152&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 176627152 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: May2024 vid: 62 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 176627152 174740812 10.1007/s11517-023-03013-8 176627152 ppf: 1409 ppct: 17 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: SSDL—an automated semi-supervised deep learning approach for patient-specific 3D reconstruction of proximal femur from QCT images. aug: au: Sultana, Jamalia Naznin, Mahmuda Faisal, Tanvir R. affil: https://ror.org/05a1qpv97 Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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