Deep learning-based dual-energy subtraction synthesis from single-energy kV x-ray fluoroscopy for markerless tumor tracking.
| Publicado en: | Medical & Biological Engineering & Computing Vol. 63; no. 12; pp. 3857 - 3873 |
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| Autores principales: | , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Dec2025
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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=189750710&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 189750710 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Dec2025 vid: 63 iid: 12 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 189750710 187546482 10.1007/s11517-025-03432-9 189750710 ppf: 3857 ppct: 16 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Deep learning-based dual-energy subtraction synthesis from single-energy kV x-ray fluoroscopy for markerless tumor tracking. aug: au: Wang, Jiaoyang Ichiji, Kei Zeng, Yuwen Zhang, Xiaoyong Takai, Yoshihiro Homma, Noriyasu affil: https://ror.org/01dq60k83 Graduate School of Biomedical Engineering, Tohoku University, Aoba-6-3 Aramaki, 980-8579, Sendai, Miyagi, Japan sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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