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Non-Negative Iterative Convex Refinement Approach for Accurate and Robust Reconstruction in Cerenkov Luminescence Tomography 期刊论文
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2020, 卷号: 39, 期号: 10, 页码: 3207-3217
作者:  Cai, Meishan;  Zhang, Zeyu;  Shi, Xiaojing;  Yang, Junying;  Hu, Zhenhua;  Tian, Jie
Adobe PDF(2176Kb)  |  收藏  |  浏览/下载：336/69  |  提交时间：2021/01/07
Image reconstruction  Imaging  Mathematical model  Shape  Slabs  Iterative methods  Luminescence  Cerenkov luminescence tomography  sparse reconstruction  inverse problem  tumor  
Radiomics in liver diseases: Current progress and future opportunities 期刊论文
LIVER INTERNATIONAL, 2020, 卷号: 40, 期号: 9, 页码: 2050-2063
作者:  Wei, Jingwei;  Jiang, Hanyu;  Gu, Dongsheng;  Niu, Meng;  Fu, Fangfang;  Han, Yuqi;  Song, Bin;  Tian, Jie
Adobe PDF(872Kb)  |  收藏  |  浏览/下载：487/134  |  提交时间：2020/08/03
data science  liver diseases  machine learning  precision medicine  radiologic technology  
Fluorescence Molecular Tomography Based on Group Sparsity Priori for Morphological Reconstruction of Glioma 期刊论文
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2020, 卷号: 67, 期号: 5, 页码: 1429-1437
作者:  Jiang, Shixin;  Liu, Jie;  An, Yu;  Gao, Yuan;  Meng, Hui;  Wang, Kun;  Tian, Jie
收藏  |  浏览/下载：265/0  |  提交时间：2020/06/22
Fluorescence  Image reconstruction  Tumors  Reconstruction algorithms  Morphology  Photonics  Inverse problems  Fluorescence molecular tomography  group sparsity  image reconstruction  morphological reconstruction  
The improved reconstruction of fluorescence molecular tomography via regularized doubly orthogonal matching pursuit method 会议论文
, Houston, USA, 2020-2-16
作者:  Lingxin Kong;  Yu An;  Yang Du;  Jie Tian
Adobe PDF(1305Kb)  |  收藏  |  浏览/下载：270/66  |  提交时间：2020/06/15
Reconstruction for Fluorescence Molecular Tomography via Adaptive Group Orthogonal Matching Pursuit 期刊论文
IEEE Transactions on Biomedical Engineering, 2020, 卷号: 67, 期号: 10.1109/TBME.2019.2963815, 页码: 1-12
作者:  Kong, Lingxin;  An, Yu;  Liang, Qian;  Yin, Lin;  Du, Yang;  Tian, Jie
浏览  |  Adobe PDF(4495Kb)  |  收藏  |  浏览/下载：299/92  |  提交时间：2020/06/03
adaptive group orthogonal matching pursuit  fluorescence molecular tomography  local spatial structured sparsity regularization  inverse problem  
Dual-energy CT-based deep learning radiomics can improve lymph node metastasis risk prediction for gastric cancer 期刊论文
EUROPEAN RADIOLOGY, 2020, 页码: 10
作者:  Li, Jing;  Dong, Di;  Fang, Mengjie;  Wang, Rui;  Tian, Jie;  Li, Hailiang;  Gao, Jianbo
Adobe PDF(1808Kb)  |  收藏  |  浏览/下载：344/52  |  提交时间：2020/03/30
Gastric cancer  Tomography  X-ray computed  Lymph node  Radiomics  Deep learning