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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:202/60  |  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:328/63  |  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  
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:417/68  |  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  
A Computational Prediction Method Based on Modified U-Net for Cell Distribution in Tumor Microenvironment 会议论文
, 线上会议, 2021-2-15
作者:  Bian, Chang;  Wang, Yu;  An, Yu;  Wang, Hanfan;  Du, Yang;  Tian, Jie
Adobe PDF(28768Kb)  |  收藏  |  浏览/下载:195/43  |  提交时间:2021/05/28
ImmunoAIzer: A Deep Learning-Based Computational Framework to Characterize Cell Distribution and Gene Mutation in Tumor Microenvironment 期刊论文
CANCERS, 2021, 卷号: 13, 期号: 7, 页码: 21
作者:  Bian, Chang;  Wang, Yu;  Lu, Zhihao;  An, Yu;  Wang, Hanfan;  Kong, Lingxin;  Du, Yang;  Tian, Jie
Adobe PDF(14076Kb)  |  收藏  |  浏览/下载:298/27  |  提交时间:2021/05/17
deep learning  cell distribution  biomarker  tumor gene mutation  tumor microenvironment (TME)  semi-supervised learning  hematoxylin and eosin (H&  E)