CFDA: Collaborative Feature Disentanglement and Augmentation for Pulmonary Airway Tree Modeling of COVID-19 CTs
In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 : 25th International Conference, Singapore, September 18–22, Jg. 13431 (2022), S. 506-516
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Zugriff:
Titel: |
CFDA: Collaborative Feature Disentanglement and Augmentation for Pulmonary Airway Tree Modeling of COVID-19 CTs
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Autor/in / Beteiligte Person: | Zhang, Minghui ; Zhang, Hanxiao ; Yang, Guang-Zhong ; Gu, Yun ; Goos, Gerhard, Founding Editor ; Hartmanis, Juris, Founding Editor ; Bertino, Elisa [Ed.]ial Board Member ; Gao, Wen [Ed.]ial Board Member ; Steffen, Bernhard [Ed.]ial Board Member ; Yung, Moti [Ed.]ial Board Member ; Wang, Linwei [Ed.] ; Dou, Qi [Ed.] ; Fletcher, P. Thomas [Ed.] ; Speidel, Stefanie [Ed.] ; Li, Shuo [Ed.] |
Zeitschrift: | Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 : 25th International Conference, Singapore, September 18–22, Jg. 13431 (2022), S. 506-516 |
Veröffentlichung: | 2022 |
Medientyp: | E-Book |
ISBN: | 978-3-031-16430-9 (print) ; 978-3-031-16431-6 (print) |
DOI: | 10.1007/978-3-031-16431-6_48 |
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