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1 Ergebnisse
1
Towards an automated Segment Anything Model (SAM) for lesio..:
, In:
2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)
,
Ahamed, S.
;
Xu, Y.
;
Dodhia, R.
... - p. 1-1 , 2023
Link:
https://doi.org/10.1109/NSSMICRTSD49126.2023.10338080
RT T1 <cTitle>2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)</cTitle>: T1 <Title>Towards an automated Segment Anything Model (SAM) for lesion segmentation in oncological PET/CT images</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10338080&Exemplar=1&LAN=DE A1 Ahamed, S. A1 Xu, Y. A1 Dodhia, R. A1 Weeks, W. A1 Ferres, J. L. A1 Rahmim, A. YR 2023 SN 2577-0829 K1 Training K1 Semiconductor device modeling K1 Image segmentation K1 Microwave integrated circuits K1 Semiconductor detectors K1 Lung cancer K1 Lung SP 1 OP 1 LK http://dx.doi.org/https://doi.org/10.1109/NSSMICRTSD49126.2023.10338080 DO https://doi.org/10.1109/NSSMICRTSD49126.2023.10338080 SF ELIB - SuUB Bremen
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