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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：265/48  |  提交时间：2023/03/20
MSMFN: An ultrasound based multi-step modality fusion network for identifying the histologic subtypes of metastatic cervical lymphadenopathy 期刊论文
IEEE Transactions on Medical Imaging, 2022, 页码: 1-13
作者:  Zheling, Meng;  Yangyang, Zhu;  Wenjing, Pang;  Jie, Tian;  Fang, Nie;  Kun, Wang
Adobe PDF(3049Kb)  |  收藏  |  浏览/下载：242/48  |  提交时间：2023/03/27
Deep learning for predicting immunotherapeutic efficacy in advanced non-small cell lung cancer patients: a retrospective study combining progression-free survival risk and overall survival risk 期刊论文
TRANSLATIONAL LUNG CANCER RESEARCH, 2022, 页码: 23
作者:  He, Bing-Xi;  Zhong, Yi-Fan;  Zhu, Yong-Bei;  Deng, Jia-Jun;  Fang, Meng-Jie;  She, Yun-Lang;  Wang, Ting-Ting;  Yang, Yang;  Sun, Xi-Wen;  Belluomini, Lorenzo;  Watanabe, Satoshi;  Dong, Di;  Tian, Jie;  Xie, Dong
Adobe PDF(3742Kb)  |  收藏  |  浏览/下载：284/36  |  提交时间：2022/06/10
Tumor biomarkers  immunotherapy  lung neoplasms  programmed cell death 1 receptor (PD-1 receptor)  biostatistics  
CEUSegNet: A Cross-Modality Lesion Segmentation Network for Contrast-Enhanced Ultrasound 会议论文
, Kolkata, India, 2022.3.28-31
作者:  Zheling MENG;  Yangyang ZHU;  Xiao FAN;  Jie TIAN;  Fang NIE;  Kun WANG
Adobe PDF(1363Kb)  |  收藏  |  浏览/下载：90/19  |  提交时间：2023/05/11
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：202/32  |  提交时间：2021/11/02
advanced gastric cancer  Borrmann classification  ensemble learning  multilayer perceptron networks  radiomics  
基于影像组学的肝细胞癌预后因子预测方法研究 学位论文
, 中国科学院自动化研究所: 中国科学院大学, 2021
作者:  顾东升
Adobe PDF(19880Kb)  |  收藏  |  浏览/下载：237/4  |  提交时间：2021/06/16
影像组学，肝细胞癌，预后因子，无创诊断，深度学习  
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：245/23  |  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)  
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：178/38  |  提交时间：2021/05/28
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：287/61  |  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  
Improved Block Sparse Bayesian Learning Method Using K-Nearest Neighbor Strategy for Accurate Tumor Morphology Reconstruction in Bioluminescence Tomography 期刊论文
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2020, 卷号: 67, 期号: 7, 页码: 2023-2032
作者:  Yin, Lin;  Wang, Kun;  Tong, Tong;  An, Yu;  Meng, Hui;  Yang, Xin;  Tian, Jie
Adobe PDF(646Kb)  |  收藏  |  浏览/下载：311/55  |  提交时间：2020/08/03
Image reconstruction  Bayes methods  Tumors  Inverse problems  Light sources  Tomography  Morphology  Bioluminescence tomography (BLT)  block sparse Bayesian learning  morphology recovery