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CT-Based Radiomic Signature as a Prognostic Factor in Stage IV ALK-Positive Non-small-cell Lung Cancer Treated With TKI Crizotinib: A Proof-of-Concept Study 期刊论文
FRONTIERS IN ONCOLOGY, 2020, 卷号: 10, 页码: 9
Authors:  Li, Hailin;  Zhang, Rui;  Wang, Siwen;  Fang, Mengjie;  Zhu, Yongbei;  Hu, Zhenhua;  Dong, Di;  Shi, Jingyun;  Tian, Jie
Favorite  |  View/Download:0/0  |  Submit date:2020/04/07
computed tomography  radiomics  non-small-cell lung cancer  tyrosine kinase inhibitor resistance  anaplastic lymphoma kinase  
Improved generative adversarial networks using the total gradient loss for the resolution enhancement of fluorescence images 期刊论文
BIOMEDICAL OPTICS EXPRESS, 2019, 卷号: 10, 期号: 9, 页码: 4742-4756
Authors:  Zhang, Chong;  Wang, Kun;  An, Yu;  He, Kunshan;  Tong, Tong;  Tian, Jie
View  |  Adobe PDF(4570Kb)  |  Favorite  |  View/Download:28/4  |  Submit date:2019/09/26
Antitumorigenic and antiangiogenic efficacy of apatinib in liver cancer evaluated by multimodality molecular imaging 期刊论文
EXPERIMENTAL AND MOLECULAR MEDICINE, 2019, 卷号: 51, 页码: 11
Authors:  Liang, Qian;  Kong, Lingxin;  Du, Yang;  Zhu, Xu;  Tian, Jie
Favorite  |  View/Download:13/0  |  Submit date:2019/12/16
Development of a radiomics nomogram based on the 2D and 3D CT features to predict the survival of non-small cell lung cancer patients 期刊论文
EUROPEAN RADIOLOGY, 2019, 卷号: 29, 期号: 5, 页码: 2196-2206
Authors:  Yang, Lifeng;  Yang, Jingbo;  Zhou, Xiaobo;  Huang, Liyu;  Zhao, Weiling;  Wang, Tao;  Zhuang, Jian;  Tian, Jie
Favorite  |  View/Download:19/0  |  Submit date:2019/07/12
Non-small cell lung cancer  Radiomics  Tomography x-ray computed  Nomogram  
Reconstruction of Fluorescence Molecular Tomography via a Fused LASSO Method Based on Group Sparsity Prior 期刊论文
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2019, 卷号: 66, 期号: 5, 页码: 1361-1371
Authors:  Jiang, Shixin;  Liu, Jie;  Zhang, Guanglei;  An, Yu;  Meng, Hui;  Gao, Yuan;  Wang, Kun;  Tian, Jie
View  |  Adobe PDF(5641Kb)  |  Favorite  |  View/Download:46/4  |  Submit date:2019/07/11
Fluorescence molecular tomography  image reconstruction  fused LASSO method  group sparsity  
Lung cancer deficient in the tumor suppressor GATA4 is sensitive to TGFBR1 inhibition 期刊论文
NATURE COMMUNICATIONS, 2019, 卷号: 10, 期号: 1, 页码: 1665
Authors:  Gao, Lei;  Hu, Yong;  Tian, Yahui;  Fan, Zhenzhen;  Wang, Kun;  Li, Hongdan;  Zhou, Qian;  Zeng, Guandi;  Hu, Xin;  Yu, Lei;  Zhou, Shiyu;  Tong, Xinyuan;  Huang, Hsinyi;  Chen, Haiquan;  Liu, Qingsong;  Liu, Wanting;  Zhang, Gong;  Zeng, Musheng;  Zhou, Guangbiao;  He, Qingyu;  Ji, Hongbin;  Chen, Liang
View  |  Adobe PDF(2284Kb)  |  Favorite  |  View/Download:39/3  |  Submit date:2019/07/12
GATA4  
Predicting EGFR mutation status in lung adenocarcinoma on computed tomography image using deep learning 期刊论文
EUROPEAN RESPIRATORY JOURNAL, 2019, 卷号: 53, 期号: 3, 页码: 11
Authors:  Wang, Shuo;  Shi, Jingyun;  Ye, Zhaoxiang;  Dong, Di;  Yu, Dongdong;  Zhou, Mu;  Liu, Ying;  Gevaert, Olivier;  Wang, Kun;  Zhu, Yongbei;  Zhou, Hongyu;  Liu, Zhenyu;  Tian, Jie
View  |  Adobe PDF(743Kb)  |  Favorite  |  View/Download:76/24  |  Submit date:2019/04/30
The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges 期刊论文
Theranostics, 2019, 卷号: 9, 期号: 5, 页码: 1303-1322
Authors:  Liu, Zhenyu;  Wang, Shuo;  Dong, Di;  Wei, Jingwei;  Fang, Cheng;  Zhou, Xuezhi;  Sun, Kai;  Li, Longfei;  Li, Bo;  Wang, Meiyun;  Tian, Jie
View  |  Adobe PDF(2057Kb)  |  Favorite  |  View/Download:60/11  |  Submit date:2019/04/30
Radiomics  Medical Imaging  Precision Diagnosis And Treatment  Oncology  
Deep learning provides a new computed tomography-based prognostic biomarker for recurrence prediction in high-grade serous ovarian cancer 期刊论文
Radiotherapy and Oncology, 2018, 期号: 132, 页码: 171-177
Authors:  Wang, Shuo;  Liu, Zhenyu;  Rong, Yu;  Zhou, Bin;  Bai, Yan;  Wei, Wei;  Wei, Wei;  Wang, Meiyun;  Guo, Yingkun;  Tian, Jie
View  |  Adobe PDF(1623Kb)  |  Favorite  |  View/Download:73/18  |  Submit date:2019/04/30
Deep Learning  High-grade Serous Ovarian Cancer  Recurrence  Prognosis  Computed Tomography  Artificial Intelligence  Semi-supervised Learning  Auto Encoder  Unsupervised Learning  
A New Approach to Predict Progression-free Survival in Stage IV EGFR-mutant NSCLC Patients with EGFR-TKI Therapy 期刊论文
CLINICAL CANCER RESEARCH, 2018, 卷号: 24, 期号: 15, 页码: 3583-3592
Authors:  Song, Jiangdian;  Shi, Jingyun;  Dong, Di;  Fang, Mengjie;  Zhong, Wenzhao;  Wang, Kun;  Wu, Ning;  Huang, Yanqi;  Liu, Zhenyu;  Cheng, Yue;  Gan, Yuncui;  Zhou, Yongzhao;  Zhou, Ping;  Chen, Bojiang;  Liang, Changhong;  Liu, Zaiyi;  Li, Weimin;  Tian, Jie
View  |  Adobe PDF(1305Kb)  |  Favorite  |  View/Download:77/4  |  Submit date:2018/10/10
EGFR-TKI therapy