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基于Renset衍生模型的多模态超声图像的应用研究 学位论文
中国科学院大学, 中国科学院自动化研究所智能化大厦9层910会议室: 中国科学院自动化研究所, 2021
Authors:  吕志坤
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超声图像,无创诊断,影像组学,深度学习  
Prediction of Microvascular Invasion in Hepatocellular Carcinoma via Deep Learning: A Multi-Center and Prospective Validation Study 期刊论文
CANCERS, 2021, 卷号: 13, 期号: 10, 页码: 19
Authors:  Wei, Jingwei;  Jiang, Hanyu;  Zeng, Mengsu;  Wang, Meiyun;  Niu, Meng;  Gu, Dongsheng;  Chong, Huanhuan;  Zhang, Yanyan;  Fu, Fangfang;  Zhou, Mu;  Chen, Jie;  Lyv, Fudong;  Wei, Hong;  Bashir, Mustafa R.;  Song, Bin;  Li, Hongjun;  Tian, Jie
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hepatocellular carcinoma  microvascular invasion  magnetic resonance imaging  computed tomography  deep learning  
Comparing radiomics models with different inputs for accurate diagnosis of significant fibrosis in chronic liver disease 期刊论文
EUROPEAN RADIOLOGY, 2021, 页码: 12
Authors:  Lu, Xue;  Zhou, Hui;  Wang, Kun;  Jin, Jieyang;  Meng, Fankun;  Mu, Xiaojie;  Li, Shuoyang;  Zheng, Rongqin;  Tian, Jie
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Liver disease  Hepatic cirrhosis  Elasticity imaging techniques  Deep learning  
Predicting Lung Cancers Using Epidemiological Data: A Generative-Discriminative Framework 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2021, 卷号: 8, 期号: 5, 页码: 1067-1078
Authors:  Jinpeng Li;  Yaling Tao;  Ting Cai
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Cancer prevention  discriminative model  generative model  lung cancer  machine learning  
Deep Convolutional Neural Network-Aided Detection of Portal Hypertension in Patients With Cirrhosis 期刊论文
CLINICAL GASTROENTEROLOGY AND HEPATOLOGY, 2020, 卷号: 18, 期号: 13, 页码: 2998-+
Authors:  Liu, Yanna;  Ning, Zhenyuan;  Ormeci, Necati;  An, Weimin;  Yu, Qian;  Han, Kangfu;  Huang, Yifei;  Liu, Dengxiang;  Liu, Fuquan;  Li, Zhiwei;  Ding, Huiguo;  Luo, Hongwu;  Zuo, Changzeng;  Liu, Changchun;  Wang, Jitao;  Zhang, Chunqing;  Ji, Jiansong;  Wang, Wenhui;  Wang, Zhiwei;  Wang, Weidong;  Yuan, Min;  Li, Lei;  Zhao, Zhongwei;  Wang, Guangchuan;  Li, Mingxing;  Liu, Qingbo;  Lei, Junqiang;  Liu, Chuan;  Tang, Tianyu;  Akcalar, Seray;  Celebioglu, Emrecan;  Ustuner, Evren;  Bilgic, Sadik;  Ellik, Zeynep;  Asiller, Ozgun Omer;  Liu, Zaiyi;  Teng, Gaojun;  Chen, Yaolong;  Hou, Jinlin;  Li, Xun;  He, Xiaoshun;  Dong, Jiahong;  Tian, Jie;  Liang, Ping;  Ju, Shenghong;  Zhang, Yu;  Qi, Xiaolong
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HVPG  Diagnostic  Deep Learning  AI  
A Deep Learning Prognosis Model Help Alert for COVID-19 Patients at High-Risk of Death: A Multi-Center Study 期刊论文
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2020, 卷号: 24, 期号: 12, 页码: 3576-3584
Authors:  Meng, Lingwei;  Dong, Di;  Li, Liang;  Niu, Meng;  Bai, Yan;  Wang, Meiyun;  Qiu, Xiaoming;  Zha, Yunfei;  Tian, Jie
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COVID-19  Computed tomography  Lung  Hospitals  Biomedical imaging  Training  Coronavirus disease 2019 (COVID-19)  prognosis  computed tomography  deep learning  artificial intelligence  
Deep Learning Radiomics Based on Contrast-Enhanced Ultrasound Might Optimize Curative Treatments for Very-Early or Early-Stage Hepatocellular Carcinoma Patients 期刊论文
LIVER CANCER, 2020, 卷号: 9, 期号: 4, 页码: 397-413
Authors:  Liu, Fei;  Liu, Dan;  Wang, Kun;  Xie, Xiaohua;  Su, Liya;  Kuang, Ming;  Huang, Guangliang;  Peng, Baogang;  Wang, Yuqi;  Lin, Manxia;  Tian, Jie;  Xie, Xiaoyan
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Contrast-enhanced ultrasound  Hepatocellular carcinoma  Radiomics  Radiofrequency ablation  Surgical resection  
Radiomics in liver diseases: Current progress and future opportunities 期刊论文
LIVER INTERNATIONAL, 2020, 卷号: 40, 期号: 9, 页码: 2050-2063
Authors:  Wei, Jingwei;  Jiang, Hanyu;  Gu, Dongsheng;  Niu, Meng;  Fu, Fangfang;  Han, Yuqi;  Song, Bin;  Tian, Jie
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data science  liver diseases  machine learning  precision medicine  radiologic technology  
MRI-Based Radiomics Signature: A Potential Biomarker for Identifying Glypican 3-Positive Hepatocellular Carcinoma 期刊论文
JOURNAL OF MAGNETIC RESONANCE IMAGING, 2020, 卷号: 52, 期号: 6, 页码: 1679-1687
Authors:  Gu, Dongsheng;  Xie, Yongsheng;  Wei, Jingwei;  Li, Wencui;  Ye, Zhaoxiang;  Zhu, Zhongyuan;  Tian, Jie;  Li, Xubin
Adobe PDF(904Kb)  |  Favorite  |  View/Download:48/0  |  Submit date:2020/07/20
glypican 3  hepatocellular carcinoma  radiomics  noninvasive  nomogram  
基于深度学习策略的超声多模态影像组学方法研究 学位论文
, 中国科学院大学自动化研究所: 中国科学院大学, 2020
Authors:  周辉
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超声成像  深度学习  影像组学  无创诊断  人工智能