| Automatic detection and classification of rib fractures on thoracic CT using convolutional neural network: accuracy and feasibility QQ Zhou, J Wang, W Tang, ZC Hu, ZY Xia, XS Li, R Zhang, X Yin, ... Korean journal of radiology 21 (7), 869, 2020 | 82 | 2020 |
| Automatic detection and classification of rib fractures based on patientsą CT images and clinical information via convolutional neural network QQ Zhou, W Tang, J Wang, ZC Hu, ZY Xia, R Zhang, X Fan, W Yong, ... European Radiology 31, 3815-3825, 2021 | 31 | 2021 |
| Identification of benign and malignant pulmonary nodules on chest CT using improved 3D U-Net deep learning framework K Yang, J Liu, W Tang, H Zhang, R Zhang, J Gu, R Zhu, J Xiong, X Ru, ... European journal of radiology 129, 109013, 2020 | 25 | 2020 |
| Precise anatomical localization and classification of rib fractures on CT using a convolutional neural network QQ Zhou, ZC Hu, W Tang, ZY Xia, J Wang, R Zhang, X Li, CY Chen, ... Clinical Imaging 81, 24-32, 2022 | 11 | 2022 |
| M-SEAM-NAM: multi-instance self-supervised equivalent attention mechanism with neighborhood affinity module for double weakly supervised segmentation of COVID-19 W Tang, H Kang, Y Cao, P Yu, H Han, R Zhang, K Chen Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 9 | 2021 |
| Highly robust prediction of lung nodule malignancy by deep learning model: A multiracial, multinational study H Wu, W Tang, C Wu, Y Deng, R Zhang medRxiv, 2020.11. 24.20237354, 2020 | 2 | 2020 |
