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CASIA OpenIR

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Deep learning-based automatic scoring models for the disease activity of rheumatoid arthritis based on multimodal ultrasound images 期刊论文
RHEUMATOLOGY, 2023, 页码: 8
作者:  He, Xuelei;  Wang, Ming;  Zhao, Chenyang;  Wang, Qian;  Zhang, Rui;  Liu, Jian;  Zhang, Yixiu;  Qi, Zhenhong;  Su, Na;  Wei, Yao;  Gui, Yang;  Li, Jianchu;  Tian, Xinping;  Zeng, Xiaofeng;  Jiang, Yuxin;  Wang, Kun;  Yang, Meng
收藏  |  浏览/下载：94/0  |  提交时间：2023/11/17
deep learning  RA  activity  scoring  multimodal ultrasonography  
Robot-Assisted Trans-Esophageal Ultrasound and the Virtual Admittance-Based Master-Slave Control Method Thereof 期刊论文
IEEE/ASME Transactions on Mechatronics, 2023, 页码: 在线发表
作者:  Xie Yiping(谢亿平);  Guo Jun(郭君);  Deng Zhaokun(邓兆锟);  Hou Xilong(侯西龙);  Housden James;  Rhode Kawal;  Liu Hongbin(刘宏斌);  Hou Zeng-Guang(侯增广);  Wang Shuangyi(王双翌)
Adobe PDF(2038Kb)  |  收藏  |  浏览/下载：267/70  |  提交时间：2023/05/31
多模态超声时空特征互作融合智能分析算法及其辅助临床诊断研究 学位论文
, 2023
作者:  孟哲令
Adobe PDF(10969Kb)  |  收藏  |  浏览/下载：162/5  |  提交时间：2023/05/18
多模态超声影像  互作融合  人工智能辅助临床诊断  多步模态融合网络  层次化诊断网络  
Enhanced glypican-3-targeted identification of hepatocellular carcinoma with liver fibrosis by pre-degrading excess fibrotic collagen 期刊论文
Acta Biomaterialia, 2023, 卷号: 158, 页码: 435- 448
作者:  Zhuo, Jiaming;  Wang, Yueqi;  Hui, Hui;  Li, Changjian;  Yang, Junying;  Zhang, Peng;  Fang, Chihua;  Tian, Jie
Adobe PDF(4667Kb)  |  收藏  |  浏览/下载：148/74  |  提交时间：2023/05/04
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：250/48  |  提交时间：2023/03/27
Deep learning radiomics of dual-modality ultrasound images for hierarchical diagnosis of unexplained cervical lymphadenopathy 期刊论文
BMC Medicine, 2022, 卷号: 20, 期号: 1, 页码: 1-13
作者:  Zhu,Yangyang;  Meng,Zheling;  Fan,Xiao;  Duan,Yin;  Jia,Yingying;  Dong,Tiantian;  Wang,Yanfang;  Song,Juan;  Tian,Jie;  Wang,Kun;  Nie,Fang
Adobe PDF(3297Kb)  |  收藏  |  浏览/下载：229/33  |  提交时间：2022/09/19
Deep learning  Cervical lymphadenopathy  Ultrasound  Reactive hyperplasia  Tuberculous lymphadenitis  Lymphoma  Metastatic carcinoma  
基于多分支网络的医学声学图像重建与分析算法研究 学位论文
, 中国科学院自动化研究所: 中国科学院自动化研究所, 2022
作者:  童同
Adobe PDF(24634Kb)  |  收藏  |  浏览/下载：272/9  |  提交时间：2022/06/13
光声断层成像  超声成像  图像重建  图像分析  多分支网络  深度学习  
Deep learning radiomics based on contrast-enhanced ultrasound images for assisted diagnosis of pancreatic ductal adenocarcinoma and chronic pancreatitis 期刊论文
BMC MEDICINE, 2022, 卷号: 20, 期号: 1, 页码: 15
作者:  Tong, Tong;  Gu, Jionghui;  Xu, Dong;  Song, Ling;  Zhao, Qiyu;  Cheng, Fang;  Yuan, Zhiqiang;  Tian, Shuyuan;  Yang, Xin;  Tian, Jie;  Wang, Kun;  Jiang, Tian'an
Adobe PDF(9703Kb)  |  收藏  |  浏览/下载：323/54  |  提交时间：2022/06/06
Deep learning  Artificial intelligence  Pancreatic ductal adenocarcinoma  Contrast-enhanced ultrasound  Chronic pancreatitis  
Deep learning radiomics of dual-energy computed tomography for predicting lymph node metastases of pancreatic ductal adenocarcinoma 期刊论文
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2021, 页码: 13
作者:  An, Chao;  Li, Dongyang;  Li, Sheng;  Li, Wangzhong;  Tong, Tong;  Liu, Lizhi;  Jiang, Dongping;  Jiang, Linling;  Ruan, Guangying;  Hai, Ning;  Fu, Yan;  Wang, Kun;  Zhuo, Shuiqing;  Tian, Jie
Adobe PDF(2925Kb)  |  收藏  |  浏览/下载：289/55  |  提交时间：2021/12/28
Lymph node metastases  Pancreatic ductal adenocarcinoma  Deep learning  Dual-energy computed tomography  Prognosis  
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：221/33  |  提交时间：2021/11/02
advanced gastric cancer  Borrmann classification  ensemble learning  multilayer perceptron networks  radiomics