Rongguo Zhang
Rongguo Zhang
Institute of Advanced Research,Infervision Medical Technology
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JCS: An explainable covid-19 diagnosis system by joint classification and segmentation
YH Wu, SH Gao, J Mei, J Xu, DP Fan, RG Zhang, MM Cheng
IEEE Transactions on Image Processing (TIP) 30, 3113-3126, 2021
Prediction of the development of pulmonary fibrosis using serial thin-section CT and clinical features in patients discharged after treatment for COVID-19 pneumonia
M Yu, Y Liu, D Xu, R Zhang, L Lan, H Xu
Korean journal of radiology 21 (6), 746, 2020
A preliminary examination of the diagnostic value of deep learning in hip osteoarthritis
Y Xue, R Zhang, Y Deng, K Chen, T Jiang
PloS one 12 (6), e0178992, 2017
Multimodal 3D DenseNet for IDH Genotype Prediction in Gliomas
S Liang, R Zhang, D Liang, T Song, T Ai, C Xia, L Xia, Y Wang
Genes 9 (8), 382, 2018
Evaluating a fully automated pulmonary nodule detection approach and its impact on radiologist performance
K Liu, Q Li, J Ma, Z Zhou, M Sun, Y Deng, W Tu, Y Wang, L Fan, C Xia, ...
Radiology. Artificial intelligence 1 (3), 2019
Deep learning-based triage and analysis of lesion burden for COVID-19: a retrospective study with external validation
M Wang, C Xia, L Huang, S Xu, C Qin, J Liu, Y Cao, P Yu, T Zhu, H Zhu, ...
The Lancet Digital Health 2 (10), e506-e515, 2020
Survey on deep learning for pulmonary medical imaging
J Ma, Y Song, X Tian, Y Hua, R Zhang, J Wu
Frontiers of medicine 14 (4), 450-469, 2020
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
Evaluation of acute pulmonary embolism and clot burden on CTPA with deep learning
W Liu, M Liu, X Guo, P Zhang, L Zhang, R Zhang, H Kang, Z Zhai, X Tao, ...
European radiology 30 (6), 3567-3575, 2020
Opportunistic osteoporosis screening in multi-detector CT images using deep convolutional neural networks
Y Fang, W Li, X Chen, K Chen, H Kang, P Yu, R Zhang, J Liao, G Hong, ...
European Radiology 31 (4), 1831-1842, 2021
Automatic detection and classification of rib fractures based on patients˘ 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 (6), 3815-3825, 2021
Multiple instance learning based method for similar handwritten Chinese characters discrimination
Y Shao, C Wang, B Xiao, R Zhang, Y Zhang
2011 International Conference on Document Analysis and Recognition, 1002-1006, 2011
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
Machine learning for pretest probability of obstructive coronary stenosis in symptomatic patients
Z Hou, B Lu, Z Li, Y An, Y Gao, W Yin, S Liang, R Zhang
JACC: Cardiovascular Imaging 12 (12), 2584-2586, 2019
Group-attention single-shot detector (ga-ssd): finding pulmonary nodules in large-scale ct images
J Ma, X Li, H Li, BH Menze, S Liang, R Zhang, WS Zheng
International Conference on Medical Imaging with Deep Learning, 358-369, 2019
Deep residual nets model for staging liver fibrosis on plain CT images
Q Li, B Yu, X Tian, X Cui, R Zhang, Q Guo
International Journal of Computer Assisted Radiology and Surgery 15 (8 …, 2020
Development of a deep learning model for classifying thymoma as Masaoka-Koga stage I or II via preoperative CT images
L Yang, W Cai, X Yang, H Zhu, Z Liu, X Wu, Y Lei, J Zou, B Zeng, X Tian, ...
Annals of Translational Medicine 8 (6), 2020
基于卷积神经网络成人肋骨骨折 CT 自动检测和分类的应用研究
周清清, 王佳硕, 唐雯, 张荣国
影像诊断与介入放射学 29 (1), 27-31, 2020
Discrimination of smoking status by MRI based on deep learning method
S Wang, R Zhang, Y Deng, K Chen, D Xiao, P Peng, T Jiang
Quantitative Imaging in Medicine and Surgery 8 (11), 1113, 2018
Quadratic-chi similarity metric learning for histogram feature
X Cai, B Xiao, C Wang, R Zhang
The First Asian Conference on Pattern Recognition, 47-51, 2011
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