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1 Ergebnisse
1
A U-Net Based Lesion Segmentation Method for Computer-Aided..:
, In:
2022 37th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC)
,
Wu, Yongfei
;
Katayama, Daisuke
;
Michida, Ryuichi
... - p. 329-332 , 2022
Link:
https://doi.org/10.1109/ITC-CSCC55581.2022.9895039
RT T1 <cTitle>2022 37th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC)</cTitle>: T1 <Title>A U-Net Based Lesion Segmentation Method for Computer-Aided Diagnosis in Colorectal NBI Endoscopy</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9895039&Exemplar=1&LAN=DE A1 Wu, Yongfei A1 Katayama, Daisuke A1 Michida, Ryuichi A1 Koide, Tetsushi A1 Tamaki, Toru A1 Yoshida, Shigeto A1 Okamoto, Yuki A1 Oka, Shiro A1 Tanaka, Shinji YR 2022 K1 Training K1 Computers K1 Image segmentation K1 Design automation K1 Endoscopes K1 Imaging K1 Medical services K1 U-Net K1 Narrow Band Imaging (NBI) K1 Computer-Aided Diagnosis (CAD) K1 Deep Learning K1 Lesion Segmentation SP 329 OP 332 LK http://dx.doi.org/https://doi.org/10.1109/ITC-CSCC55581.2022.9895039 DO https://doi.org/10.1109/ITC-CSCC55581.2022.9895039 SF ELIB - SuUB Bremen
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