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Dual-stream Representation Fusion Learning for accurate medical image segmentation 期刊论文
Engineering Applications of Artificial Intelligence, 2023, 卷号: 123, 页码: 106402
作者:  Xu RT(许镕涛);  Wang CW(王常维);  Xu SB(徐士彪);  Meng WL(孟维亮);  Zhang XP(张晓鹏)
Adobe PDF(1893Kb)  |  收藏  |  浏览/下载：191/53  |  提交时间：2023/05/18
Patient-level grading prediction of prostate cancer from mp-MRI via GMINet 期刊论文
COMPUTERS IN BIOLOGY AND MEDICINE, 2022, 卷号: 150, 页码: 10
作者:  Shao, Lizhi;  Liu, Zhenyu;  Liu, Jiangang;  Yan, Ye;  Sun, Kai;  Liu, Xiangyu;  Lu, Jian;  Tian, Jie
收藏  |  浏览/下载：169/0  |  提交时间：2022/11/21
mp-MRI  Prostate cancer  Grade group  Patient-level prediction  Deep learning  
CellNet: A Lightweight Model towards Accurate LOC-Based High-Speed Cell Detection 期刊论文
ELECTRONICS, 2022, 卷号: 11, 期号: 9, 页码: 20
作者:  Long, Xianlei;  Ishii, Idaku;  Gu, Qingyi
Adobe PDF(1681Kb)  |  收藏  |  浏览/下载：340/165  |  提交时间：2022/07/25
cell detection  high-speed vision  convolutional neural network (CNN)  efficient convolutional block  medical image analysis  
Deep learning radiomics of ultrasonography can predict response to neoadjuvant chemotherapy in breast cancer at an early stage of treatment: a prospective study 期刊论文
EUROPEAN RADIOLOGY, 2021, 页码: 11
作者:  Gu, Jionghui;  Tong, Tong;  He, Chang;  Xu, Min;  Yang, Xin;  Tian, Jie;  Jiang, Tianan;  Wang, Kun
Adobe PDF(3007Kb)  |  收藏  |  浏览/下载：249/45  |  提交时间：2021/12/28
Breast cancer  Deep learning  Neoadjuvant chemotherapy  Ultrasonography  Treatment outcome  
Identifying early gastric cancer under magnifying narrow-band images with deep learning: a multicenter study 期刊论文
GASTROINTESTINAL ENDOSCOPY, 2021, 卷号: 93, 期号: 6, 页码: 1333-+
作者:  Hu, Hao;  Gong, Lixin;  Dong, Di;  Zhu, Liang;  Wang, Min;  He, Jie;  Shu, Lei;  Cai, Yiling;  Cai, Shilun;  Su, Wei;  Zhong, Yunshi;  Li, Cong;  Zhu, Yongbei;  Fang, Mengjie;  Zhong, Lianzhen;  Yang, Xin;  Zhou, Pinghong;  Tian, Jie
Adobe PDF(2330Kb)  |  收藏  |  浏览/下载：256/51  |  提交时间：2021/08/15
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：333/60  |  提交时间：2021/05/17
Fluorescence imaging  Deep learning  Convolutional neural networks  Intraoperative pathology  Gliomas  
CT-based radiomics to predict development of macrovascular invasion in hepatocellular carcinoma: A multicenter study 期刊论文
Hepatobiliary & Pancreatic Diseases International, 2021, 卷号: 2021, 期号: --, 页码: --
作者:  Jingwei Wei;  Sirui Fu;  Jie Zhang;  Dongsheng Gu;  Xiaoqun Li;  Xudong Chen;  Shuaitong Zhang;  Xiaofei He;  Jianfeng Yan;  Ligong Lu;  Jie Tian
Adobe PDF(1564Kb)  |  收藏  |  浏览/下载：148/34  |  提交时间：2022/04/06
Computed tomography  Hepatocellular carcinoma  Macrovascular invasion  Prognosis  Radiomics  
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：173/34  |  提交时间：2021/06/16
molecular imaging, machine learning, artificial intelligence  
CT-based deep learning radiomics analysis for evaluation of serosa invasion in advanced gastric cancer 期刊论文
EUROPEAN JOURNAL OF RADIOLOGY, 2020, 卷号: 132, 页码: 8
作者:  Sun, Rui-Jia;  Fang, Meng-Jie;  Tang, Lei;  Li, Xiao-Ting;  Lu, Qiao-Yuan;  Dong, Di;  Tian, Jie;  Sun, Ying-Shi
Adobe PDF(3491Kb)  |  收藏  |  浏览/下载：264/49  |  提交时间：2021/01/06
Stomach neoplasms  Multi-detector computed tomography  Radiomics  Deep learning  
A radiomics model for preoperative prediction of brain invasion in meningioma non-invasively based on MRI: A multicentre study 期刊论文
EBIOMEDICINE, 2020, 卷号: 58, 页码: 11
作者:  Zhang, Jing;  Yao, Kuan;  Liu, Panpan;  Liu, Zhenyu;  Han, Tao;  Zhao, Zhiyong;  Cao, Yuntai;  Zhang, Guojin;  Zhang, Junting;  Tian, Jie;  Zhou, Junlin
收藏  |  浏览/下载：186/0  |  提交时间：2020/12/04
Meningioma  Brain invasion  Radiomics  Magnetic resonance images