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Deep Learning Architectures for Medical Image Segmentation:
, In:
2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS)
,
Subramaniam, Sudha
;
Jayanthi, K.B.
;
Rajasekaran, C.
. - p. 579-584 , 2020
Link:
https://doi.org/10.1109/CBMS49503.2020.00115
RT T1 <cTitle>2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS)</cTitle>: T1 <Title>Deep Learning Architectures for Medical Image Segmentation</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9182808&Exemplar=1&LAN=DE A1 Subramaniam, Sudha A1 Jayanthi, K.B. A1 Rajasekaran, C. A1 Kuchelar, Ramani YR 2020 SN 2372-9198 K1 Image segmentation K1 Feature extraction K1 Computer architecture K1 Training K1 Medical diagnostic imaging K1 Data mining K1 Convolutional neural network, Segmentation, Attention module, U-Net SP 579 OP 584 LK http://dx.doi.org/https://doi.org/10.1109/CBMS49503.2020.00115 DO https://doi.org/10.1109/CBMS49503.2020.00115 SF ELIB - SuUB Bremen
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