ResDAC-Net: a novel pancreas segmentation model utilizing residual double asymmetric spatial kernels.
| Publicado en: | Medical & Biological Engineering & Computing Vol. 62; no. 7; pp. 2087 - 2101 |
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| Autores principales: | , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jul2024
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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=177992398&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 177992398 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Jul2024 vid: 62 iid: 7 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 177992398 175892643 10.1007/s11517-024-03052-9 177992398 ppf: 2087 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: ResDAC-Net: a novel pancreas segmentation model utilizing residual double asymmetric spatial kernels. aug: au: Ji, Zhanlin Liu, Jianuo Mu, Juncheng Zhang, Haiyang Dai, Chenxu Yuan, Na Ganchev, Ivan affil: https://ror.org/04z4wmb81 Department of Artificial Intelligence, North China University of Science and Technology, 063009, Tangshan, China sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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