Deep learning-based automatic cranial implant design through direct defect shape prediction and its comparison study.
| Publicado en: | Medical & Biological Engineering & Computing Vol. 63; no. 9; pp. 2815 - 2827 |
|---|---|
| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Sep2025
|
| 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=187673853&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 187673853 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Sep2025 vid: 63 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 187673853 184858597 10.1007/s11517-025-03363-5 187673853 ppf: 2815 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Deep learning-based automatic cranial implant design through direct defect shape prediction and its comparison study. aug: au: Memon, Afaque Rafique Shi, Haochen Memon, Tarique Rafique Egger, Jan Chen, Xiaojun affil: https://ror.org/0220qvk04 School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
|---|