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1 Ergebnisse
1
A Deep Learning-Facilitated Radiomics Solution for the Pred..:
, In:
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)
,
Chen, Antong
;
Saouaf, Jennifer
;
Zhou, Bo
... - p. 678-682 , 2020
Link:
https://doi.org/10.1109/ISBI45749.2020.9098561
RT T1 <cTitle>2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)</cTitle>: T1 <Title>A Deep Learning-Facilitated Radiomics Solution for the Prediction of Lung Lesion Shrinkage in Non-Small Cell Lung Cancer Trials</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9098561&Exemplar=1&LAN=DE A1 Chen, Antong A1 Saouaf, Jennifer A1 Zhou, Bo A1 Crawford, Randolph A1 Yuan, Jianda A1 Ma, Junshui A1 Baumgartner, Richard A1 Wang, Shubing A1 Goldmacher, Gregory YR 2020 SN 1945-8452 K1 Lesions K1 Feature extraction K1 Lung K1 Computed tomography K1 Three-dimensional displays K1 Cancer K1 Fractals K1 radiomics K1 convolutional neural networks K1 segmentation K1 quantitative vessel tortuosity SP 678 OP 682 LK http://dx.doi.org/https://doi.org/10.1109/ISBI45749.2020.9098561 DO https://doi.org/10.1109/ISBI45749.2020.9098561 SF ELIB - SuUB Bremen
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