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Adaptive Grouping Block Sparse Bayesian Learning Method for Accurate and Robust Reconstruction in Bioluminescence Tomography 期刊论文
IEEE Transactions on Biomedical Engineering, 2021, 卷号: 68, 期号: 99, 页码: 1
作者:  Yin, Lin;  Wang, Kun;  Tong, Tong;  Wang, Qian;  An, Yu;  Yang, Xin;  Tian, Jie
Adobe PDF(11700Kb)  |  收藏  |  浏览/下载：297/53  |  提交时间：2021/05/31
adaptive grouping  bioluminescence tomography  block sparse Bayesian learning  
Deep Learning Radiomics Based on Contrast-Enhanced Ultrasound Might Optimize Curative Treatments for Very-Early or Early-Stage Hepatocellular Carcinoma Patients 期刊论文
LIVER CANCER, 2020, 卷号: 9, 期号: 4, 页码: 397-413
作者:  Liu, Fei;  Liu, Dan;  Wang, Kun;  Xie, Xiaohua;  Su, Liya;  Kuang, Ming;  Huang, Guangliang;  Peng, Baogang;  Wang, Yuqi;  Lin, Manxia;  Tian, Jie;  Xie, Xiaoyan
浏览  |  Adobe PDF(1066Kb)  |  收藏  |  浏览/下载：406/104  |  提交时间：2020/09/07
Contrast-enhanced ultrasound  Hepatocellular carcinoma  Radiomics  Radiofrequency ablation  Surgical resection  
Radiomic signature: A novel magnetic resonance imaging-based prognostic biomarker in patients with skull base chordoma 期刊论文
RADIOTHERAPY AND ONCOLOGY, 2019, 卷号: 141, 页码: 239-246
作者:  Wei, Wei;  Wang, Ke;  Liu, Zhenyu;  Tian, Kaibing;  Wang, Liang;  Du, Jiang;  Ma, Junpeng;  Wang, Shuo;  Li, Longfei;  Zhao, Rui;  Cui, Luo;  Wu, Zhen;  Tian, Jie
收藏  |  浏览/下载：407/0  |  提交时间：2020/03/30
Biomarkers  Magnetic resonance imaging  Prognosis  Progression-free survival  Radiomics  Skull base chordoma  
A Non-invasive Radiomic Method Using F-18-FDG PET Predicts Isocitrate Dehydrogenase Genotype and Prognosis in Patients With Glioma 期刊论文
FRONTIERS IN ONCOLOGY, 2019, 卷号: 9, 页码: 11
作者:  Li, Longfei;  Mu, Wei;  Wang, Yaning;  Liu, Zhenyu;  Liu, Zehua;  Wang, Yu;  Ma, Wenbin;  Kong, Ziren;  Wang, Shuo;  Zhou, Xuezhi;  Wei, Wei;  Cheng, Xin;  Lin, Yusong;  Tian, Jie
收藏  |  浏览/下载：350/0  |  提交时间：2020/03/30
F-18-FDG PET  radiomics  glioma  isocitrate dehydrogenase  non-invasive prediction  
Application of machine learning method in optical molecular imaging: a review 期刊论文
SCIENCE CHINA-INFORMATION SCIENCES, 2020, 卷号: 63, 期号: 1, 页码: 16
作者:  An, Yu;  Meng, Hui;  Gao, Yuan;  Tong, Tong;  Zhang, Chong;  Wang, Kun;  Tian, Jie
Adobe PDF(5942Kb)  |  收藏  |  浏览/下载：377/63  |  提交时间：2020/03/30
optical molecular imaging  machine learning  artificial intelligence  
Radiomic analysis for pretreatment prediction of response to neoadjuvant chemotherapy in locally advanced cervical cancer: A multicentre study 期刊论文
EBIOMEDICINE, 2019, 卷号: 46, 页码: 160-169
作者:  Sun, Caixia;  Tian, Xin;  Liu, Zhenyu;  Li, Weili;  Li, Pengfei;  Chen, Jiaming;  Zhang, Weifeng;  Fang, Ziyu;  Du, Peiyan;  Duan, Hui;  Liu, Ping;  Wang, Lihui;  Chen, Chunlin;  Tian, Jie
收藏  |  浏览/下载：325/0  |  提交时间：2019/12/16
Radiomics  Magnetic resonance imaging  Neoadjuvant chemotherapy  Locally advanced cervical cancer  
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
作者:  Zhang, Chong;  Wang, Kun;  An, Yu;  He, Kunshan;  Tong, Tong;  Tian, Jie
浏览  |  Adobe PDF(4570Kb)  |  收藏  |  浏览/下载：290/85  |  提交时间：2019/09/26
A Computed Tomography-Based Radiomic Prognostic Marker of Advanced High-Grade Serous Ovarian Cancer Recurrence: A Multicenter Study 期刊论文
FRONTIERS IN ONCOLOGY, 2019, 卷号: 9, 页码: 12
作者:  Wei, Wei;  Liu, Zhenyu;  Rong, Yu;  Zhou, Bin;  Bei, Yan;  Wei, Wei;  Wang, Shuo;  Wang, Meiyun;  Guo, Yingkun;  Tian, Jie
收藏  |  浏览/下载：326/0  |  提交时间：2019/07/12
advanced high-grade serous ovarian cancer  CT  prognosis  radiomics  recurrence  
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
作者:  Jiang, Shixin;  Liu, Jie;  Zhang, Guanglei;  An, Yu;  Meng, Hui;  Gao, Yuan;  Wang, Kun;  Tian, Jie
浏览  |  Adobe PDF(5641Kb)  |  收藏  |  浏览/下载：552/128  |  提交时间：2019/07/11
Fluorescence molecular tomography  image reconstruction  fused LASSO method  group sparsity