mm3DSNet: multi-scale and multi-feedforward self-attention 3D segmentation network for CT scans of hepatobiliary ducts.
| Publicado en: | Medical & Biological Engineering & Computing Vol. 63; no. 1; pp. 127 - 139 |
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| Autores principales: | , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jan2025
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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=182077535&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 182077535 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Jan2025 vid: 63 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 182077535 179163346 10.1007/s11517-024-03183-z 182077535 ppf: 127 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: mm3DSNet: multi-scale and multi-feedforward self-attention 3D segmentation network for CT scans of hepatobiliary ducts. aug: au: Zhou, Yinghong Xie, Yiying Cai, Nian Liang, Yuchen Gong, Ruifeng Wang, Ping affil: https://ror.org/04azbjn80 School of Information Engineering, Guangdong University of Technology, 510006, Guangzhou, China sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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