Adaptive ensemble loss and multi-scale attention in breast ultrasound segmentation with UMA-Net.
| Publicado en: | Medical & Biological Engineering & Computing Vol. 63; no. 6; pp. 1697 - 1714 |
|---|---|
| Autores principales: | , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jun2025
|
| 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=185423484&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 185423484 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Jun2025 vid: 63 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 185423484 182379968 10.1007/s11517-025-03301-5 185423484 ppf: 1697 ppct: 17 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Adaptive ensemble loss and multi-scale attention in breast ultrasound segmentation with UMA-Net. aug: au: Dar, Mohsin Furkh Ganivada, Avatharam affil: https://ror.org/04a7rxb17 Artificial Intelligence Lab, School of Computer and Information Sciences, University of Hyderabad, 500046, Hyderabad, India sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
|---|