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Deep learning radiomics of ultrasonography can predict response to neoadjuvant chemotherapy in breast cancer at an early stage of treatment: a prospective study 期刊论文
EUROPEAN RADIOLOGY, 2021, 页码: 11
作者:  Gu, Jionghui;  Tong, Tong;  He, Chang;  Xu, Min;  Yang, Xin;  Tian, Jie;  Jiang, Tianan;  Wang, Kun
Adobe PDF(3007Kb)  |  收藏  |  浏览/下载:279/49  |  提交时间:2021/12/28
Breast cancer  Deep learning  Neoadjuvant chemotherapy  Ultrasonography  Treatment outcome  
Cascaded one-shot deformable convolutional neural networks: Developing a deep learning model for respiratory motion estimation in ultrasound sequences 期刊论文
Medical Image Analysis, 2020, 卷号: 65, 期号: 65, 页码: 101793
作者:  Fei Liu;  Dan Liu;  Jie Tian;  Xiaoyan Xie;  Xin Yang;  Wang K(王坤)
浏览  |  Adobe PDF(3180Kb)  |  收藏  |  浏览/下载:200/56  |  提交时间:2020/11/02
Ultrasound sequence  Respiratory motion estimation  Cascaded Siamese network  One-shot deformable convolution  
Improved Block Sparse Bayesian Learning Method Using K-Nearest Neighbor Strategy for Accurate Tumor Morphology Reconstruction in Bioluminescence Tomography 期刊论文
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2020, 卷号: 67, 期号: 7, 页码: 2023-2032
作者:  Yin, Lin;  Wang, Kun;  Tong, Tong;  An, Yu;  Meng, Hui;  Yang, Xin;  Tian, Jie
浏览  |  Adobe PDF(646Kb)  |  收藏  |  浏览/下载:334/59  |  提交时间:2020/08/03
Image reconstruction  Bayes methods  Tumors  Inverse problems  Light sources  Tomography  Morphology  Bioluminescence tomography (BLT)  block sparse Bayesian learning  morphology recovery  
Non-invasive genotype prediction of chromosome 1p/19q co-deletion by development and validation of an MRI-based radiomics signature in lower-grade gliomas 期刊论文
JOURNAL OF NEURO-ONCOLOGY, 2018, 卷号: 140, 期号: 2, 页码: 297-306
作者:  Han, Yuqi;  Xie, Zhen;  Zang, Yali;  Zhang, Shuaitong;  Gu, Dongsheng;  Zhou, Mu;  Gevaert, Olivier;  Wei, Jingwei;  Li, Chao;  Chen, Hongyan;  Du, Jiang;  Liu, Zhenyu;  Dong, Di;  Tian, Jie;  Zhou, Dabiao
浏览  |  Adobe PDF(2365Kb)  |  收藏  |  浏览/下载:507/151  |  提交时间:2019/07/12
Lower-grade glioma  1p19q Co-deletion  Prediction  Radiomics  Magnetic resonance imaging  
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:527/123  |  提交时间:2019/07/11
Fluorescence molecular tomography  image reconstruction  fused LASSO method  group sparsity