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A systematic 3-D magnetic particle imaging simulation model for quantitative analysis of reconstruction image quality 期刊论文
Computer Methods and Programs in Biomedicine, 2024, 卷号: 252, 页码: 108250-108250
作者:  Yusong Shen;  Liwen Zhang;  Hui Hui;  Lishuang Guo;  Tan Wang;  Guanyu Yang;  Jie Tian
Adobe PDF(6711Kb)  |  收藏  |  浏览/下载：11/5  |  提交时间：2024/06/11
A Streamlined 3-D Magnetic Particle Imaging System With a Two-Stage Excitation Feed-Through Compensation Strategy 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2023, 卷号: 72, 页码: 1-10
作者:  Yin L(尹琳);  Li W(李玮);  Bian ZW(卞忠伟);  Chen ZW(陈梓威);  Liu YJ(刘晏君);  Zhong J(钟景);  Zhang SX(张水兴);  Du Y(杜洋);  Hui H(惠辉);  Tian J(田捷)
Adobe PDF(3893Kb)  |  收藏  |  浏览/下载：53/24  |  提交时间：2024/03/26
3-D imaging  compensation strategy  magnetic particle imaging (MPI)  
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：69/2  |  提交时间：2024/02/22
Magnetic particle imaging  deep learning  self-attention mechanism  time-frequency spectrum  background signal  
First Clinical Investigation of Near-Infrared Window IIa/IIb Fluorescence Imaging for Precise Surgical Resection of Gliomas 期刊论文
IEEE Transactions on Biomedical Engineering, 2022, 卷号: 69, 页码: 2404-2413
作者:  Caiguang Cao;  Zeping Jin;  Xiaojing Shi;  Zhe Zhang;  Anqi Xiao;  Junying Yang;  Nan Ji;  Jie Tian;  Zhenhua Hu
Adobe PDF(4444Kb)  |  收藏  |  浏览/下载：171/58  |  提交时间：2023/06/14
PP-NAS: Searching for Plug-and-Play Blocks on Convolutional Neural Network 会议论文
, Montreal, BC, Canada, 11-17 October 2021
作者:  Shen, Biluo;  Xiao, Anqi;  Tian, Jie;  Hu, Zhenhua
Adobe PDF(235Kb)  |  收藏  |  浏览/下载：203/40  |  提交时间：2022/06/15
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：207/62  |  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：332/63  |  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  
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：243/6  |  提交时间：2022/06/06
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：283/59  |  提交时间：2021/11/02
COVID-19  deep learning  radiomics  prognosis  computed tomography  
Specific Borrmann classification in advanced gastric cancer by an ensemble multilayer perceptron network: a multicenter research 期刊论文
MEDICAL PHYSICS, 2021, 卷号: 48, 期号: 9, 页码: 5017-5028
作者:  Wang, Siwen;  Dong, Di;  Zhang, Wenjuan;  Hu, Hui;  Li, Hailin;  Zhu, Yongbei;  Zhou, Junlin;  Shan, Xiuhong;  Tian, Jie
Adobe PDF(2265Kb)  |  收藏  |  浏览/下载：269/40  |  提交时间：2021/11/02
advanced gastric cancer  Borrmann classification  ensemble learning  multilayer perceptron networks  radiomics