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PGNet: Projection generative network for sparse-view reconstruction of projection-based magnetic particle imaging 期刊论文
MEDICAL PHYSICS, 2022, 页码: 18
作者:  Wu, Xiangjun;  He, Bingxi;  Gao, Pengli;  Zhang, Peng;  Shang, Yaxin;  Zhang, Liwen;  Zhong, Jing;  Jiang, Jingying;  Hui, Hui;  Tian, Jie
收藏  |  浏览/下载：203/0  |  提交时间：2022/11/21
deep learning  field-free line  magnetic particle imaging  sparse view  
graph convolution based residual connected network for morphological reconstruction in fluorescence molecular tomography 会议论文
, 美国, 2022-2
作者:  Wang Y(王宇);  Bian C(边畅);  Du Y(杜洋);  Tian J(田捷)
Adobe PDF(625Kb)  |  收藏  |  浏览/下载：187/58  |  提交时间：2022/06/14
Fluorescence molecular tomography  Graph convolution network  
A Fast and Automated FMT/XCT Reconstruction Strategy Based on Standardized Imaging Space 期刊论文
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2022, 卷号: 41, 期号: 3, 页码: 657-666
作者:  An, Yu;  Bian, Chang;  Yan, Daxiang;  Wang, Hanfan;  Wang, Yu;  Du, Yang;  Tian, Jie
Adobe PDF(8285Kb)  |  收藏  |  浏览/下载：307/59  |  提交时间：2022/06/06
Imaging  Image reconstruction  Mice  In vivo  Image segmentation  Finite element analysis  Surface reconstruction  Fluorescence molecular tomography  imaging reconstruction  standardized imaging space  
A Deep Learning Radiomics Model to Identify Poor Outcome in COVID-19 Patients With Underlying Health Conditions: A Multicenter Study 期刊论文
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2021, 卷号: 25, 期号: 7, 页码: 2353-2362
作者:  Wang, Siwen;  Dong, Di;  Li, Liang;  Li, Hailin;  Bai, Yan;  Hu, Yahua;  Huang, Yuanyi;  Yu, Xiangrong;  Liu, Sibin;  Qiu, Xiaoming;  Lu, Ligong;  Wang, Meiyun;  Zha, Yunfei;  Tian, Jie
Adobe PDF(3142Kb)  |  收藏  |  浏览/下载：257/53  |  提交时间：2021/11/02
COVID-19  deep learning  radiomics  prognosis  computed tomography  
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：186/36  |  提交时间：2021/06/16
molecular imaging, machine learning, artificial intelligence  
A Novel Adaptive Parameter Search Elastic Net Method for Fluorescent Molecular Tomography 期刊论文
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2021, 卷号: 40, 期号: 5, 页码: 1484-1498
作者:  Wang, Hanfan;  Bian, Chang;  Kong, Lingxin;  An, Yu;  Du, Yang;  Tian, Jie
Adobe PDF(8176Kb)  |  收藏  |  浏览/下载：386/60  |  提交时间：2021/06/15
Image reconstruction  Fluorescence  Probes  Mathematical model  Photonics  Molecular imaging  Biological tissues  Fluorescence molecular tomography  adaptive parameter search  elastic net  
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：168/15  |  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：253/47  |  提交时间：2021/05/31
adaptive grouping  bioluminescence tomography  block sparse Bayesian learning  
Integrating No.3 lymph nodes and primary tumor radiomics to predict lymph node metastasis in T1-2 gastric cancer 期刊论文
BMC Medical Imaging, 2021, 卷号: 21, 期号: 1, 页码: 10
作者:  Wang,Xiaoxiao;  Li,Cong;  Fang,Mengjie;  Zhang,Liwen;  Zhong,Lianzhen;  Dong,Di;  Tian,Jie;  Shan,Xiuhong
Adobe PDF(2269Kb)  |  收藏  |  浏览/下载：388/61  |  提交时间：2021/04/06
Stomach cancer  Lymph nodes  Nomogram  
Classification of Severe and Critical Covid-19 Using Deep Learning and Radiomics 期刊论文
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2020, 卷号: 24, 期号: 12, 页码: 3585-3594
作者:  Li, Cong;  Dong, Di;  Li, Liang;  Gong, Wei;  Li, Xiaohu;  Bai, Yan;  Wang, Meiyun;  Hu, Zhenhua;  Zha, Yunfei;  Tian, Jie
Adobe PDF(2325Kb)  |  收藏  |  浏览/下载：317/53  |  提交时间：2021/03/02
COVID-19  radiomics  deep learning  computed tomography (CT)