I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
Deep learning approaches for automated classification and s..:
Badrigilan, Samireh
;
Nabavi, Shahabedin
;
Abin, Ahmad Ali
...
International Journal of Computer Assisted Radiology and Surgery. 16 (2021) 4 - p. 529-542 , 2021
Link:
https://doi.org/10.1007/s11548-021-02326-z
RT Journal T1 <Title>Deep learning approaches for automated classification and segmentation of head and neck cancers and brain tumors in magnetic resonance images: a meta-analysis study</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1007_s11548-021-02326-z&Exemplar=1&LAN=DE A1 Badrigilan, Samireh A1 Nabavi, Shahabedin A1 Abin, Ahmad Ali A1 Rostampour, Nima A1 Abedi, Iraj A1 Shirvani, Atefeh A1 Ebrahimi Moghaddam, Mohsen PB Springer Science and Business Media LLC YR 2021 SN 1861-6410 SN 1861-6429 JF International Journal of Computer Assisted Radiology and Surgery VO 16 IS 4 SP 529 OP 542 LK http://dx.doi.org/https://doi.org/10.1007/s11548-021-02326-z DO https://doi.org/10.1007/s11548-021-02326-z SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
