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1 Ergebnisse
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Comprehensive deep learning-based framework for automatic o..:
Czipczer, Vanda
;
Kolozsvári, Bernadett
;
Deák-Karancsi, Borbála
...
Frontiers in Physics. 11 (2023) - p. , 2023
Link:
https://doi.org/10.3389/fphy.2023.1236792
RT Journal T1
Comprehensive deep learning-based framework for automatic organs-at-risk segmentation in head-and-neck and pelvis for MR-guided radiation therapy planning
UL https://suche.suub.uni-bremen.de/peid=cr-10.3389_fphy.2023.1236792&Exemplar=1&LAN=DE A1 Czipczer, Vanda A1 Kolozsvári, Bernadett A1 Deák-Karancsi, Borbála A1 Capala, Marta E. A1 Pearson, Rachel A. A1 Borzási, Emőke A1 Együd, Zsófia A1 Gaál, Szilvia A1 Kelemen, Gyöngyi A1 Kószó, Renáta A1 Paczona, Viktor A1 Végváry, Zoltán A1 Karancsi, Zsófia A1 Kékesi, Ádám A1 Czunyi, Edina A1 Irmai, Blanka H. A1 Keresnyei, Nóra G. A1 Nagypál, Petra A1 Czabány, Renáta A1 Gyalai, Bence A1 Tass, Bulcsú P. A1 Cziria, Balázs A1 Cozzini, Cristina A1 Estkowsky, Lloyd A1 Ferenczi, Lehel A1 Frontó, András A1 Maxwell, Ross A1 Megyeri, István A1 Mian, Michael A1 Tan, Tao PB Frontiers Media SA YR 2023 SN 2296-424X JF Frontiers in Physics VO 11 LK http://dx.doi.org/https://doi.org/10.3389/fphy.2023.1236792 DO https://doi.org/10.3389/fphy.2023.1236792 SF ELIB - SuUB Bremen
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