PuSH - Publication Server of Helmholtz Zentrum München: Deep-learning based estimation of loco-regional control for patients with locally advanced HNSCC.

Navigation

Home

Deutsch

Research

Advanced Search

Browse by ...

... Journal

... Publication Type

... Research Data

... Publication Year

Publication overview

Support & Contact

Contact persons

Help

Data protection

Starke, S.* ; Leger, S.* ; Zwanenburg, A.* ; Pilz, K.* ; Lohaus, F.* ; Linge, A.* ; Zoephel, K.* ; Kotzerke, J.* ; Schreiber, A.* ; Tinhofer, I.* ; Budach, V.* ; Stuschke, M.* ; Balermpas, P.* ; Roedel, C.* ; Ganswindt, U. ; Belka, C. ; Pigorsch, S.* ; Combs, S.E. ; Moennich, D.* ; Zips, D.* ; Krause, M.* ; Baumann, M.* ; Richter, C.* ; Troost, E.G.C.* ; Loeck, S.*

Deep-learning based estimation of loco-regional control for patients with locally advanced HNSCC.

Radiother. Oncol. 133, S254-S255 (2019)

Open Access Green as soon as Postprint is submitted to ZB.

Abstract
Metrics
Extra information

Additional Metrics?

[➜Log in]

Edit extra informations Login

Publication type Article: Journal article

Document type Meeting abstract

Corresponding Author

ISSN (print) / ISBN 0167-8140

e-ISSN 1879-0887

Journal Radiotherapy and Oncology

Quellenangaben Volume: 133, Pages: S254-S255

Publisher Elsevier

Publishing Place Elsevier House, Brookvale Plaza, East Park Shannon, Co, Clare, 00000, Ireland

Non-patent literature Publications

Reviewing status Peer reviewed

Institute(s) CCG Personalized Radiotherapy in Head and Neck Cancer (KKG-KRT)
Institute of Radiation Medicine (IRM)