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CNN-based Whole Breast Segmentation in Longitudinal High-ri..:
, In:
Informatik aktuell; Bildverarbeitung für die Medizin 2023
,
Ambroladze, Ani
;
Hahn, Horst K.
;
Amer, Heba
... - p. 159-164 , 2023
Link:
https://doi.org/10.1007/978-3-658-41657-7_35
RT T1 <cTitle>Informatik aktuell; Bildverarbeitung für die Medizin 2023</cTitle>: T1 <Title>CNN-based Whole Breast Segmentation in Longitudinal High-risk MRI Study: Initial Findings on Quality vs. Quantity of Training Annotations</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1007_978-3-658-41657-7_35&Exemplar=1&LAN=DE A1 Ambroladze, Ani A1 Hahn, Horst K. A1 Amer, Heba A1 Ingrisch, Michael A1 Gerken, Annika A1 Wenzel, Markus A1 Püsken, Michael A1 Mittermeier, Andreas A1 Engel, Christoph A1 Schmutzler, Rita A1 Fallenberg, Eva M. PB Springer Fachmedien Wiesbaden YR 2023 SP 159 OP 164 LK http://dx.doi.org/https://doi.org/10.1007/978-3-658-41657-7_35 DO https://doi.org/10.1007/978-3-658-41657-7_35 SF ELIB - SuUB Bremen
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