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BSS-TFNet: Attention-Enhanced Background Signal Suppression Network for Time-Frequency Spectrum in Magnetic Particle Imaging 期刊论文
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE, 2023, 页码: 15
作者:  Wei, Zechen;  Liu, Yanjun;  Zhu, Tao;  Yang, Xin;  Tian, Jie;  Hui, Hui
Adobe PDF(6094Kb)  |  收藏  |  浏览/下载：102/5  |  提交时间：2024/02/22
Magnetic particle imaging  deep learning  self-attention mechanism  time-frequency spectrum  background signal  
Plexin D1 mediates disturbed flow-induced M1 macrophage polarization in atherosclerosis 期刊论文
HELIYON, 2023, 卷号: 9, 期号: 6, 页码: 15
作者:  Zhang, Suhui;  Zhang, Yingqian;  Zhang, Peng;  Wei, Zechen;  Ma, Mingrui;  Wang, Wei;  Tong, Wei;  Tian, Feng;  Hui, Hui;  Tian, Jie;  Chen, Yundai
Adobe PDF(8914Kb)  |  收藏  |  浏览/下载：152/8  |  提交时间：2023/11/17
Plexin D1  Macrophage polarization  Disturbed flow  Bifurcation lesions  Atherosclerosis  
Magnetic particle imaging deblurring with dual contrastive learning and adversarial framework 期刊论文
COMPUTERS IN BIOLOGY AND MEDICINE, 2023, 卷号: 165, 页码: 11
作者:  Zhang, Jiaxin;  Wei, Zechen;  Wu, Xiangjun;  Shang, Yaxin;  Tian, Jie;  Hui, Hui
Adobe PDF(6341Kb)  |  收藏  |  浏览/下载：200/17  |  提交时间：2023/11/16
Magnetic particle imaging  Deblurring  Unpaired data  Contrastive learning  Adversarial framework  
Excitation-based fully connected network for precise NIR-II fluorescence molecular tomography 期刊论文
BIOMEDICAL OPTICS EXPRESS, 2022, 卷号: 13, 期号: 12, 页码: 6284-6299
作者:  Cao, Caiguang;  Xiao, Anqi;  Cai, Meishan;  Shen, Biluo;  Guo, Lishuang;  Shi, Xiaojing;  Tian, Jie;  Hu, Zhenhua
Adobe PDF(6713Kb)  |  收藏  |  浏览/下载：475/58  |  提交时间：2023/03/20
A multi-scale, multi-region and attention mechanism-based deep learning framework for prediction of grading in hepatocellular carcinoma 期刊论文
MEDICAL PHYSICS, 2022, 页码: 13
作者:  Wei, Jingwei;  Ji, Qian;  Gao, Yu;  Yang, Xiaozhen;  Guo, Donghui;  Gu, Dongsheng;  Yuan, Chunwang;  Tian, Jie;  Ding, Dawei
收藏  |  浏览/下载：400/0  |  提交时间：2023/03/20
computed tomography  deep learning  hepatocellular carcinoma  histopathological grading  radiomics  
The Detection of Divalent Iron and Reactive Oxygen Species During Ferroptosis with the Use of a Dual-Reaction Turn-On Fluorescent Probe 期刊论文
MOLECULAR IMAGING AND BIOLOGY, 2022, 页码: 12
作者:  Wang, Yueqi;  Li, Changjian;  Zhuo, Jiaming;  Hui, Hui;  Zhou, Bing;  Tian, Jie
Adobe PDF(1924Kb)  |  收藏  |  浏览/下载：387/104  |  提交时间：2022/11/14
Dual-reaction  Fe(II)  Ferroptosis  Fluorescent probes  ROS  Turn-on response  
Lineage Tracing and Molecular Real-Time Imaging of Cancer Stem Cells 期刊论文
BIOSENSORS-BASEL, 2022, 卷号: 12, 期号: 9, 页码: 13
作者:  Jia, Xiaohua;  Shen, Guodong;  Jia, Jia;  Zhang, Yan;  Zhang, Dan;  Li, Wanjun;  Zhang, Jianjun;  Huang, Xinglu;  Tian, Jie
Adobe PDF(580Kb)  |  收藏  |  浏览/下载：277/13  |  提交时间：2022/11/14
lineage tracing  molecular imaging  cancer stem cells  
Heterogeneous Knowledge Learning of Predictive Academic Intelligence in Transportation 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 卷号: 23, 期号: 4, 页码: 3737-3755
作者:  Lu, Hao;  Zhu, Yifan;  Lin, Qika;  Wang, Tan;  Niu, Zhendong;  Herrera-Viedma, Enrique
收藏  |  浏览/下载：258/0  |  提交时间：2022/06/10
Academic impact prediction  predictive knowledge analytics  transportation research  heterogeneous knowledge learning  academic intelligence  social transportation  
Elimination of stripe artifacts in light sheet fluorescence microscopy using an attention-based residual neural network 期刊论文
BIOMEDICAL OPTICS EXPRESS, 2022, 卷号: 13, 期号: 3, 页码: 1292-1311
作者:  Wei, Zechen;  Wu, Xiangjun;  Tong, Wei;  Zhang, Suhui;  Yang, Xin;  Tian, Jie;  Hui, Hui
Adobe PDF(6522Kb)  |  收藏  |  浏览/下载：270/16  |  提交时间：2022/06/06
Structure attention co-training neural network for neovascularization segmentation in intravascular optical coherence tomography 期刊论文
MEDICAL PHYSICS, 2022, 页码: 16
作者:  Wu, Xiangjun;  Zhang, Yingqian;  Zhang, Peng;  Hui, Hui;  Jing, Jing;  Tian, Feng;  Jiang, Jingying;  Yang, Xin;  Chen, Yundai;  Tian, Jie
收藏  |  浏览/下载：238/0  |  提交时间：2022/03/17
co-training  IVOCT  neovascularization segmentation  structural attention mechanism