CASIA OpenIR
(本次检索基于用户作品认领结果)

浏览/检索结果: 共19条,第1-10条 帮助

限定条件        
已选(0)清除 条数/页:   排序方式:
A review of the application of machine learning in molecular imaging 期刊论文
Annals of Translational Medicine, 2021, 卷号: 0, 期号: 0, 页码: 0
作者:  Yin, Lin;  Cao, Zhen;  Wang, Kun;  Tian, Jie;  Yang, Xing;  Zhang, Jianhua
Adobe PDF(4435Kb)  |  收藏  |  浏览/下载:187/36  |  提交时间:2021/06/16
molecular imaging, machine learning, artificial intelligence  
Gaussian weighted block sparse Bayesian learning strategy based on K-means clustering algorithm for accurate bioluminescence tomography in glioma 会议论文
, 线上, 2021.2.15-2021.2.19
作者:  Yin, Lin;  Wang, Kun;  Tian, Jie
Adobe PDF(6162Kb)  |  收藏  |  浏览/下载:170/15  |  提交时间:2021/05/31
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:256/47  |  提交时间:2021/05/31
adaptive grouping  bioluminescence tomography  block sparse Bayesian learning  
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:328/58  |  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  
K-nearest Neighbor Based Locally Connected Network for Fast Morphological Reconstruction in Fluorescence Molecular Tomography 期刊论文
IEEE Transactions on Medical Imaging, 2020, 卷号: 无, 期号: 无, 页码: 无
作者:  Meng, Hui;  Gao, Yuan;  Yang, Xin;  Wang, Kun;  Tian, Jie
浏览  |  Adobe PDF(4698Kb)  |  收藏  |  浏览/下载:288/73  |  提交时间:2020/04/29
Fluorescence Tomography  Machine Learning  Brain  
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:345/57  |  提交时间:2020/03/30
optical molecular imaging  machine learning  artificial intelligence  
Reconstruction method for fluorescence molecular tomography based on L1-norm primal accelerated proximal gradient 期刊论文
Journal of Biomedical Optics, 2018, 卷号: 23, 期号: 8, 页码: 085002
作者:  Yuhao Liu;  Shixin Jiang;  Jie Liu;  Yu An;  Guanglei Zhang;  Yuan Gao;  Wang K(王坤);  Jie Tian
浏览  |  Adobe PDF(4066Kb)  |  收藏  |  浏览/下载:238/68  |  提交时间:2019/09/26
Fluorescence Molecular Tomography  Image-reconstruction  Diffuse Optical Tomography  
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:523/121  |  提交时间:2019/07/11
Fluorescence molecular tomography  image reconstruction  fused LASSO method  group sparsity  
Fast and Robust Reconstruction Method for Fluorescence Molecular Tomography based on Deep Neural Network 会议论文
, The Moscone Center, San Francisco, California, USA, 2019-02-02
作者:  Huang C(黄超);  Meng Hui;  Yuan Gao;  Shixin Jiang;  Kun Wang;  Jie Tian
浏览  |  Adobe PDF(587Kb)  |  收藏  |  浏览/下载:364/147  |  提交时间:2019/04/29
Fluorescence Molecular Tomography, Ill-poseness, Deep Convolution Neural Network, Reconstruction.  
Non model-based bioluminescence tomography using a machine-learning reconstruction strategy 期刊论文
Optica, 2018, 卷号: 5, 期号: 11, 页码: 1451-1454
作者:  Gao, Yuan;  Wang, Kun;  An, Yu;  Jiang, Shixin;  Meng, Hui;  Tian, Jie
浏览  |  Adobe PDF(708Kb)  |  收藏  |  浏览/下载:231/29  |  提交时间:2019/04/29
Light  Regularization  Registration  Information  Algorithm  Accuracy