mResU-Net: multi-scale residual U-Net-based brain tumor segmentation from multimodal MRI.
| Publicado en: | Medical & Biological Engineering & Computing Vol. 62; no. 3; pp. 641 - 652 |
|---|---|
| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Mar2024
|
| 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=175566366&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 175566366 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Mar2024 vid: 62 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 175566366 173686499 10.1007/s11517-023-02965-1 175566366 ppf: 641 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: mResU-Net: multi-scale residual U-Net-based brain tumor segmentation from multimodal MRI. aug: au: Li, Pengcheng Li, Zhihao Wang, Zijian Li, Chaoxiang Wang, Monan affil: https://ror.org/04e6y1282 School of Mechanical and Power Engineering, Harbin University of Science and Technology, 150000, Harbin, Heilongjiang, China sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
|---|