DCNet: Densely Connected Neural Network with Global Context for Abnormalities Prediction in Bronchoscopy Images-Reference-Cited by-同舟云学术

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DCNet: Densely Connected Neural Network with Global Context for Abnormalities Prediction in Bronchoscopy Images

Published:2023-12-05 Issue: Volume:30 Page:3566-3573
ISSN:
Container-title:2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
language:
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Author:

Wang Ying¹,Tie Yun¹,Liu Fenghui²,Qi Lin¹,Hu Ziqing³

Affiliation:

1. Zhengzhou University,School of Electrical and Information Engineering,Zhengzhou,China

2. Zhengzhou University,The First Affiliated Hospital of Zhengzhou University,Zhengzhou,China

3. University of Notre Dame,Department of Applied and Computational Mathematics and Statistics,Notre Dame,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10385250/10385251/10385847.pdf?arnumber=10385847

Reference24 articles.

1. Cancer statistics for African American/Black People 2022

2. Mo1579 Duration of Endoscopic Examination Significantly Impacts Detection Rates of Neoplastic Lesions During Diagnostic Upper Endoscopy

3. Deep learning for anatomical interpretation of video bronchoscopy images

4. Development and validation of the artificial intelligence (AI)-based diagnostic model for bronchial lumen identification

5. Weakly supervised airway orifice segmentation in video bronchoscopy

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