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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：289/57  |  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  
基于块稀疏贝叶斯框架的生物自发荧光断层成像算法研究 学位论文
, 北京市海淀区中关村东路95号中国科学院自动化研究所: 中国科学院大学, 2021
作者:  尹琳
Adobe PDF(75998Kb)  |  收藏  |  浏览/下载：225/5  |  提交时间：2021/06/16
生物自发荧光断层成像  块稀疏贝叶斯算法  K均值聚类策略  K近邻策略  自适应分组策略  
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：239/52  |  提交时间：2021/11/02
COVID-19  deep learning  radiomics  prognosis  computed tomography  
Real-time intraoperative glioma diagnosis using fluorescence imaging and deep convolutional neural networks 期刊论文
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2021, 卷号: 48, 期号: 11, 页码: 3482-3492
作者:  Shen, Biluo;  Zhang, Zhe;  Shi, Xiaojing;  Cao, Caiguang;  Zhang, Zeyu;  Hu, Zhenhua;  Ji, Nan;  Tian, Jie
Adobe PDF(1209Kb)  |  收藏  |  浏览/下载：343/61  |  提交时间：2021/05/17
Fluorescence imaging  Deep learning  Convolutional neural networks  Intraoperative pathology  Gliomas  
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：179/34  |  提交时间：2021/06/16
molecular imaging, machine learning, artificial intelligence  
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：247/46  |  提交时间：2021/05/31
adaptive grouping  bioluminescence tomography  block sparse Bayesian learning  
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：299/62  |  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  
NIR-II/NIR-I Fluorescence Molecular Tomography of Heterogeneous Mice Based on Gaussian Weighted Neighborhood Fused Lasso Method 期刊论文
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2020, 卷号: 39, 期号: 6, 页码: 2213-2222
作者:  Cai, Meishan;  Zhang, Zeyu;  Shi, Xiaojing;  Hu, Zhenhua;  Tian, Jie
Adobe PDF(2134Kb)  |  收藏  |  浏览/下载：326/69  |  提交时间：2020/08/03
Fluorescence molecular tomography  NIR-II  NIR-I  GWNFL method  
基于结构相关正交匹配追踪的激发荧光肝肿瘤重建研究 学位论文
, 自动化研究所: 中国科学院大学, 2020
作者:  孔令鑫
Adobe PDF(2986Kb)  |  收藏  |  浏览/下载：268/6  |  提交时间：2020/06/03
激发荧光断层成像  匹配追踪  组稀疏  斯密特正交化  
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：267/80  |  提交时间：2020/06/03
adaptive group orthogonal matching pursuit  fluorescence molecular tomography  local spatial structured sparsity regularization  inverse problem