基本信息
刘振宇  男  博导  中国科学院自动化研究所
电子邮件: zhenyu.liu@ia.ac.cn
通信地址: 北京市海淀区中关村东路95号智能化大厦903
邮政编码:

研究领域

人工智能,模式识别,医学影像大数据分析

招生信息

   
招生专业
081104-模式识别与智能系统
招生方向
人工智能,模式识别,医学影像大数据分析

教育背景

2009-09--2014-07   中国科学院大学   博士学位
2005-09--2009-07   中国科学技术大学   学士学位

工作经历

   
工作简历
2019-11~现在, 中国科学院自动化研究所, 研究员
2016-11~2019-10,中国科学院自动化研究所, 副研究员
2014-07~2016-10,中国科学院自动化研究所, 助理研究员
社会兼职
2018-10-01-2023-10-01,中国研究型医院学会医学影像与人工智能专委会, 副主任委员

专利与奖励

   
专利成果
[1] 田捷, 尹琳, 杜洋, 刘振宇, 惠辉, 王坤. 基于自注意力机制的MMPI混合信号分离方法. 202210478647.7, 2022-05-05.

出版信息

   
发表论文
[1] Caixia Sun, Bingbing Li, Genxia Wei, Weihao Qiu, Danyi Li, Xiangzhao Li, Xiangyu Liu, Wei Wei, Shuo Wang, Zhenyu Liu, Jie Tian, Li Liang. Deep learning with whole slide images can improve the prognostic risk stratification with stage III colorectal cancer. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE. 2022, 221: [2] 马梦航, 魏炜, 刘振宇, 田捷. 人工智能在结直肠癌医学影像中的临床应用. 肿瘤影像学[J]. 2022, 31(2): 97-104, http://lib.cqvip.com/Qikan/Article/Detail?id=7107114334.
[3] Zhou, Hongyu, Li, Lu, Liu, Zhenyu, Zhao, Kankan, Chen, Xiuyu, Lu, Minjie, Yin, Gang, Song, Lei, Zhao, Shihua, Zheng, Hairong, Tian, Jie. Deep learning algorithm to improve hypertrophic cardiomyopathy mutation prediction using cardiac cine images. EUROPEAN RADIOLOGY[J]. 2021, 31(6): 3931-3940, http://dx.doi.org/10.1007/s00330-020-07454-9.
[4] Mo, Jiajie, Wei, Wei, Liu, Zhenyu, Zhang, Jianguo, Ma, Yanshan, Sang, Lin, Hu, Wenhan, Zhang, Chao, Wang, Yao, Wang, Xiu, Liu, Chang, Zhao, Baotian, Gao, Dongmei, Tian, Jie, Zhang, Kai. Neuroimaging Phenotyping and Assessment of Structural-Metabolic-Electrophysiological Alterations in the Temporal Neocortex of Focal Cortical Dysplasia IIIa. JOURNAL OF MAGNETIC RESONANCE IMAGING[J]. 2021, 54(3): 925-935, http://dx.doi.org/10.1002/jmri.27615.
[5] Zhang, Jing, Yao, Kuan, Liu, Panpan, Liu, Zhenyu, Han, Tao, Zhao, Zhiyong, Cao, Yuntai, Zhang, Guojin, Zhang, Junting, Tian, Jie, Zhou, Junlin. A radiomics model for preoperative prediction of brain invasion in meningioma non-invasively based on MRI: A multicentre study. EBIOMEDICINE[J]. 2020, 58: http://dx.doi.org/10.1016/j.ebiom.2020.102933.
[6] Qingxia Wu, Kuan Yao, Zhenyu Liu, Longfei Li, Xin Zhao, Shuo Wang, Honglei Shang, Yusong Lin, Zejun Wen, Xiaoan Zhang, Jie Tian, Meiyun Wang. Erratum to ‘Radiomics analysis of placenta on T2WI facilitates prediction of postpartum haemorrhage: A multicentre study’. EBIOMEDICINE[J]. 2020, 55: http://dx.doi.org/10.1016/j.ebiom.2020.102773.
[7] Tian, Xin, Sun, Caixia, Liu, Zhenyu, Li, Weili, Duan, Hui, Wang, Lu, Fan, Huijian, Li, Mingwei, Li, Pengfei, Wang, Lihui, Liu, Ping, Tian, Jie, Chen, Chunlin. Prediction of Response to Preoperative Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer Using Multicenter CT-Based Radiomic Analysis. FRONTIERS IN ONCOLOGY[J]. 2020, 10: [8] Xiong, Qianqian, Zhou, Xuezhi, Liu, Zhenyu, Lei, Chuqian, Yang, Ciqiu, Yang, Mei, Zhang, Liulu, Zhu, Teng, Zhuang, Xiaosheng, Liang, Changhong, Liu, Zaiyi, Tian, Jie, Wang, Kun. Multiparametric MRI-based radiomics analysis for prediction of breast cancers insensitive to neoadjuvant chemotherapy. CLINICAL & TRANSLATIONAL ONCOLOGY[J]. 2020, 22(1): 50-59, [9] Shao, Lizhi, Liu, Zhenyu, Feng, Lili, Lou, Xiaoying, Li, Zhenhui, Zhang, XiaoYan, Zhou, Xuezhi, Sun, Kai, Zhang, DaFu, Wu, Lin, Yang, Guanyu, Sun, YingShi, Xu, Ruihua, Wan, Xiangbo, Fan, Xinjuan, Tian, Jie. Radiopathomics strategy combining multiparametric MRI with whole-slide image for pretreatment prediction of tumor regression grade to neoadjuvant chemoradiotherapy in rectal cancer. CANCER RESEARCH[J]. 2020, 80(16): https://www.webofscience.com/wos/woscc/full-record/WOS:000590059300276.
[10] Guo, Xu, Liu, Zhenyu, Sun, Caixia, Zhang, Lei, Wang, Ying, Li, Ziyao, Shi, Jiaxin, Wu, Tong, Cui, Hao, Zhang, Jing, Tian, Jie, Tian, Jiawei. Deep learning radiomics of ultrasonography: Identifying the risk of axillary non-sentinel lymph node involvement in primary breast cancer. EBIOMEDICINE[J]. 2020, 60: http://dx.doi.org/10.1016/j.ebiom.2020.103018.
[11] Wang, Yinyan, Wei, Wei, Liu, Zhenyu, Liang, Yuchao, Liu, Xing, Li, Yiming, Tang, Zhenchao, Jiang, Tao, Tian, Jie. Predicting the Type of Tumor-Related Epilepsy in Patients With Low-Grade Gliomas: A Radiomics Study. FRONTIERSINONCOLOGY[J]. 2020, 10: https://doaj.org/article/4e3e00bcce84496fabb9da518c4675e9.
[12] Zhou, Xuezhi, Yi, Yongju, Liu, Zhenyu, Zhou, Zhiyang, Lai, Bingjia, Sun, Kai, Li, Longfei, Huang, Liyu, Feng, Yanqiu, Cao, Wuteng, Tian, Jie. Radiomics-Based Preoperative Prediction of Lymph Node Status Following Neoadjuvant Therapy in Locally Advanced Rectal Cancer. FRONTIERS IN ONCOLOGY[J]. 2020, 10: https://doaj.org/article/cbec7634973045f5b36e2e1df7b9aa2d.
[13] Zhou, Xuezhi, Liu, Zhenyu, Du, Yang, Xiong, Qianqian, Wang, Kun, Tian, Jie. Radiomics improved pre-therapeutic prediction of breast cancers insensitive to neoadjuvant chemotherapy. CANCER RESEARCH[J]. 2020, 80(4): http://dx.doi.org/10.1158/1538-7445.SABCS19-P1-10-29.
[14] Zhuang, Xiaosheng, Chen, Chi, Liu, Zhenyu, Zhang, Liulu, Zhou, Xuezhi, Cheng, Minyi, Ji, Fei, Zhu, Teng, Lei, Chuqian, Zhang, Junsheng, Jiang, Jingying, Tian, Jie, Wang, Kun. Multiparametric MRI-based radiomics analysis for the prediction of breast tumor regression patterns after neoadjuvant chemotherapy. TRANSLATIONAL ONCOLOGY[J]. 2020, 13(11): http://dx.doi.org/10.1016/j.tranon.2020.100831.
[15] Shao, Lizhi, Liu, Zhenyu, Feng, Lili, Lou, Xiaoying, Li, Zhenhui, Zhang, XiaoYan, Wan, Xiangbo, Zhou, Xuezhi, Sun, Kai, Zhang, DaFu, Wu, Lin, Yang, Guanyu, Sun, YingShi, Xu, Ruihua, Fan, Xinjuan, Tian, Jie. Multiparametric MRI and Whole Slide Image-Based Pretreatment Prediction of Pathological Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer: A Multicenter Radiopathomic Study. ANNALS OF SURGICAL ONCOLOGY[J]. 2020, 27(11): 4296-4306, http://dx.doi.org/10.1245/s10434-020-08659-4.
[16] Fang, Jin, Zhang, Bin, Wang, Shuo, Jin, Yan, Wang, Fei, Ding, Yingying, Chen, Qiuying, Chen, Liting, Li, Yueyue, Li, Minmin, Chen, Zhuozhi, Liu, Lizhi, Liu, Zhenyu, Tian, Jie, Zhang, Shuixing. Association of MRI-derived radiomic biomarker with disease-free survival in patients with early-stage cervical cancer. THERANOSTICS[J]. 2020, 10(5): 2284-2292, https://www.webofscience.com/wos/woscc/full-record/WOS:000508008300020.
[17] Wu, Qingxia, Wang, Shuo, Zhang, Shuixing, Wang, Meiyun, Ding, Yingying, Fang, Jin, Wu, Qingxia, Qian, Wei, Liu, Zhenyu, Sun, Kai, Jin, Yan, Ma, He, Tian, Jie. Development of a Deep Learning Model to Identify Lymph Node Metastasis on Magnetic Resonance Imaging in Patients With Cervical Cancer. JAMA NETWORK OPEN[J]. 2020, 3(7): http://dx.doi.org/10.1001/jamanetworkopen.2020.11625.
[18] Zhenyu Liu, Xiaochun Meng, Hongmei Zhang, Zhenhui Li, Jiangang Liu, Kai Sun, Yankai Meng, Weixing Dai, Peiyi Xie, Yingying Ding, Meiyun Wang, Guoxiang Cai, Jie Tian. Predicting distant metastasis and chemotherapy benefit in locally advanced rectal cancer. NATURE COMMUNICATIONS[J]. 2020, 11(1): http://dx.doi.org/10.1038/s41467-020-18162-9.
[19] Zhou, Xuezhi, Liu, Zhenyu, Zhang, Dafu, Wu, Lin, Sun, Kai, Shao, Lizhi, Huang, Liyu, Li, Zhenhui, Tian, Jie. Improving initial nodal staging of T3 rectal cancer using quantitative image features. BRITISH JOURNAL OF SURGERY. 2020, 107(11): E541-E542, http://dx.doi.org/10.1002/bjs.12027.
[20] Shao, Lizhi, Yan, Ye, Liu, Zhenyu, Ye, Xiongjun, Xia, Haizhui, Zhu, Xuehua, Zhang, Yuting, Zhang, Zhiying, Chen, Huiying, He, Wei, Liu, Cheng, Lu, Min, Huang, Yi, Ma, Lulin, Sun, Kai, Zhou, Xuezhi, Yang, Guanyu, Lu, Jian, Tian, Jie. Radiologist-like artificial intelligence for grade group prediction of radical prostatectomy for reducing upgrading and downgrading from biopsy. THERANOSTICS[J]. 2020, 10(22): 10200-10212, https://www.webofscience.com/wos/woscc/full-record/WOS:000596762400001.
[21] Wang, Ying, Sun, Kai, Liu, Zhenyu, Chen, Guanmao, Jia, Yanbin, Zhong, Shuming, Pan, Jiyang, Huang, Li, Tian, Jie. Classification of Unmedicated Bipolar Disorder Using Whole-Brain Functional Activity and Connectivity: A Radiomics Analysis. CEREBRAL CORTEX[J]. 2020, 30(3): 1117-1128, https://www.webofscience.com/wos/woscc/full-record/WOS:000535899500020.
[22] Sun, Kai, Liu, Zhenyu, Li, Yiming, Wang, Lei, Tang, Zhenchao, Wang, Shuo, Zhou, Xuezhi, Shao, Lizhi, Sun, Caixia, Liu, Xing, Jiang, Tao, Wang, Yinyan, Tian, Jie. Radiomics Analysis of Postoperative Epilepsy Seizures in Low-Grade Gliomas Using Preoperative MR Images. FRONTIERS IN ONCOLOGY[J]. 2020, 10: https://doaj.org/article/1d544ee4d8cf426590b29325aee153f7.
[23] Wu, Qingxia, Yao, Kuan, Liu, Zhenyu, Li, Longfei, Zhao, Xin, Wang, Shuo, Shang, Honglei, Lin, Yusong, Wen, Zejun, Zhang, Xiaoan, Tian, Jie, Wang, Meiyun. Radiomics analysis of placenta on T2WI facilitates prediction of postpartum haemorrhage: A multicentre study (vol 50, pg 355, 2019). EBIOMEDICINE. 2020, 55: https://www.webofscience.com/wos/woscc/full-record/WOS:000537270600008.
[24] Lei, Chuqian, Wei, Wei, Liu, Zhenyu, Xiong, Qianqian, Yang, Ciqiu, Yang, Mei, Zhang, Liulu, Zhu, Teng, Zhuang, Xiaosheng, Liu, Chunling, Liu, Zaiyi, Tian, Jie, Wang, Kun. Mammography-based radiomic analysis for predicting benign BI-RADS category 4 calcifications. EUROPEAN JOURNAL OF RADIOLOGY[J]. 2019, 121: http://dx.doi.org/10.1016/j.ejrad.2019.108711.
[25] Wei, Wei, Wang, Ke, Liu, Zhenyu, Tian, Kaibing, Wang, Liang, Du, Jiang, Ma, Junpeng, Wang, Shuo, Li, Longfei, Zhao, Rui, Cui, Luo, Wu, Zhen, Tian, Jie. Radiomic signature: A novel magnetic resonance imaging-based prognostic biomarker in patients with skull base chordoma. RADIOTHERAPY AND ONCOLOGY[J]. 2019, 141: 239-246, http://dx.doi.org/10.1016/j.radonc.2019.10.002.
[26] Wang Shuo, Chen Xi, Liu Zhenyu, Wu Qingxia, Zhu Yongbei, Wang Meiyun, Tian Jie, Mori K, Hahn HK. Radiomics analysis on T2-MR image to predict lymphovascular space invasion in cervical cancer. MEDICAL IMAGING 2019: COMPUTER-AIDED DIAGNOSISnull. 2019, 10950: [27] Kong, Ziren, Lin, Yusong, Jiang, Chendan, Li, Longfei, Liu, Zehua, Wang, Yuekun, Dai, Congxin, Liu, Delin, Qin, Xuying, Wang, Yu, Liu, Zhenyu, Cheng, Xin, Tian, Jie, Ma, Wenbin. F-18-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma. CANCER IMAGING[J]. 2019, 19(1): https://www.webofscience.com/wos/woscc/full-record/WOS:000486718800001.
[28] He, Ming, Liu, Zhenyu, Lin, Yusong, Wan, Jianzhong, Li, Juan, Xu, Kai, Wang, Yun, Jin, Zhengyu, Tian, Jie, Xue, Huadan. Differentiation of atypical non-functional pancreatic neuroendocrine tumor and pancreatic ductal adenocarcinoma using CT based radiomics. EUROPEAN JOURNAL OF RADIOLOGY[J]. 2019, 117: 102-111, http://dx.doi.org/10.1016/j.ejrad.2019.05.024.
[29] Tian, Yuan, Liu, Zhenyu, Tang, Zhenchao, Li, Mingge, Lou, Xin, Dong, Enqing, Liu, Gang, Wang, Yulin, Wang, Yan, Bian, Xiangbin, Wei, Shihui, Tian, Jie, Ma, Lin. Radiomics Analysis of DTI Data to Assess Vision Outcome After Intravenous Methylprednisolone Therapy in Neuromyelitis Optic Neuritis. JOURNAL OF MAGNETIC RESONANCE IMAGING[J]. 2019, 49(5): 1365-1373, http://ir.ia.ac.cn/handle/173211/24954.
[30] Han, Lu, Zhu, Yongbei, Liu, Zhenyu, Yu, Tao, He, Cuiju, Jiang, Wenyan, Kan, Yangyang, Dong, Di, Tian, Jie, Luo, Yahong. Radiomic nomogram for prediction of axillary lymph node metastasis in breast cancer. EUROPEAN RADIOLOGY[J]. 2019, 29(7): 3820-3829, http://ir.ia.ac.cn/handle/173211/24392.
[31] Qu, Jinrong, Shen, Chen, Qin, Jianjun, Wang, Zhaoqi, Liu, Zhenyu, Guo, Jia, Zhang, Hongkai, Gao, Pengrui, Bei, Tianxia, Wang, Yingshu, Liu, Hui, Kamel, Ihab R, Tian, Jie, Li, Hailiang. The MR radiomic signature can predict preoperative lymph node metastasis in patients with esophageal cancer. EUROPEAN RADIOLOGY[J]. 2019, 29(2): 906-914, http://ir.ia.ac.cn/handle/173211/25633.
[32] Wei, Wei, Liu, Zhenyu, Rong, Yu, Zhou, Bin, Bei, Yan, Wei, Wei, Wang, Shuo, Wang, Meiyun, Guo, Yingkun, Tian, Jie. A Computed Tomography-Based Radiomic Prognostic Marker of Advanced High-Grade Serous Ovarian Cancer Recurrence: A Multicenter Study. FRONTIERS IN ONCOLOGY[J]. 2019, 9: http://ir.ia.ac.cn/handle/173211/24952.
[33] Liu, Zhenyu, Li, Zhuolin, Qu, Jinrong, Zhang, Renzhi, Zhou, Xuezhi, Li, Longfei, Sun, Kai, Tang, Zhenchao, Jiang, Hui, Li, Hailiang, Xiong, Qianqian, Ding, Yingying, Zhao, Xinming, Wang, Kun, Liu, Zaiyi, Tian, Jie. Radiomics of Multiparametric MRI for Pretreatment Prediction of Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer: A Multicenter Study. CLINICAL CANCER RESEARCH[J]. 2019, 25(12): 3538-3547, [34] Zhou, Xuezhi, Yi, Yongju, Liu, Zhenyu, Cao, Wuteng, Lai, Bingjia, Sun, Kai, Li, Longfei, Zhou, Zhiyang, Feng, Yanqiu, Tian, Jie. Radiomics-Based Pretherapeutic Prediction of Non-response to Neoadjuvant Therapy in Locally Advanced Rectal Cancer. ANNALS OF SURGICAL ONCOLOGY[J]. 2019, 26(6): 1676-1684, http://ir.ia.ac.cn/handle/173211/24200.
[35] Kong, Z, Li, J, Liu, Zehua, Liu, Zhenyu, Zhao, D, Cheng, X, Li, L, Lin, Y, Wang, Y, Tian, J, Ma, W. Radiomics signature based on FDG-PET predicts proliferative activity in primary glioma. CLINICAL RADIOLOGY[J]. 2019, 74(10): 815.e15-815.e23, http://dx.doi.org/10.1016/j.crad.2019.06.019.
[36] Wu, Qingxia, Yao, Kuan, Liu, Zhenyu, Li, Longfei, Zhao, Xin, Wang, Shuo, Shang, Honglei, Lin, Yusong, Wen, Zejun, Tian, Jie, Wang, Meiyun. Radiomics analysis of placenta on T2WI facilitates prediction of postpartum haemorrhage: A multicentre study. EBIOMEDICINE[J]. 2019, 50: 355-365, http://dx.doi.org/10.1016/j.ebiom.2019.11.010.
[37] Li, Longfei, Mu, Wei, Wang, Yaning, Liu, Zhenyu, Liu, Zehua, Wang, Yu, Ma, Wenbin, Kong, Ziren, Wang, Shuo, Zhou, Xuezhi, Wei, Wei, Cheng, Xin, Lin, Yusong, Tian, Jie. A Non-invasive Radiomic Method Using F-18-FDG PET Predicts Isocitrate Dehydrogenase Genotype and Prognosis in Patients With Glioma. FRONTIERS IN ONCOLOGY[J]. 2019, 9: https://www.webofscience.com/wos/woscc/full-record/WOS:000501792200001.
[38] Wu, Qingxia, Wang, Shuo, Chen, Xi, Wang, Yan, Dong, Li, Liu, Zhenyu, Tian, Jie, Wang, Meiyun. Radiomics analysis of magnetic resonance imaging improves diagnostic performance of lymph node metastasis in patients with cervical cancer. RADIOTHERAPY AND ONCOLOGY[J]. 2019, 138: 141-148, http://dx.doi.org/10.1016/j.radonc.2019.04.035.
[39] Ziren Kong, Yusong Lin, Chendan Jiang, Longfei Li, Zehua Liu, Yuekun Wang, Congxin Dai, Delin Liu, Xuying Qin, Yu Wang, Zhenyu Liu, Xin Cheng, Jie Tian, Wenbin Ma. 18F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma. CANCER IMAGING[J]. 2019, 19(1): 1-10, http://dx.doi.org/10.1186/s40644-019-0246-0.
[40] Li, Longfei, Wang, Ke, Ma, Xiujian, Liu, Zhenyu, Wang, Shuo, Du, Jiang, Tian, Kaibing, Zhou, Xuezhi, Wei, Wei, Sun, Kai, Lin, Yusong, Wu, Zhen, Tian, Jie. Radiomic analysis of multiparametric magnetic resonance imaging for differentiating skull base chordoma and chondrosarcoma. EUROPEAN JOURNAL OF RADIOLOGY[J]. 2019, 118: 81-87, http://dx.doi.org/10.1016/j.ejrad.2019.07.006.
[41] Fu, Sirui, Wei, Jingwei, Zhang, Jie, Dong, Di, Song, Jiangdian, Li, Yong, Duan, Chongyang, Zhang, Shuaitong, Li, Xiaoqun, Gu, Dongsheng, Chen, Xudong, Hao, Xiaohan, He, Xiaofeng, Yan, Jianfeng, Liu, Zhenyu, Tian, Jie, Lu, Ligong. Selection Between Liver Resection Versus Transarterial Chemoembolization in Hepatocellular Carcinoma: A Multicenter Study. CLINICAL AND TRANSLATIONAL GASTROENTEROLOGY[J]. 2019, 10(8): https://www.webofscience.com/wos/woscc/full-record/WOS:000487054100001.
[42] Sun, Caixia, Tian, Xin, Liu, Zhenyu, Li, Weili, Li, Pengfei, Chen, Jiaming, Zhang, Weifeng, Fang, Ziyu, Du, Peiyan, Duan, Hui, Liu, Ping, Wang, Lihui, Chen, Chunlin, Tian, Jie. Radiomic analysis for pretreatment prediction of response to neoadjuvant chemotherapy in locally advanced cervical cancer: A multicentre study. EBIOMEDICINE[J]. 2019, 46: 160-169, http://dx.doi.org/10.1016/j.ebiom.2019.07.049.
[43] Liu, Zhenyu, Liu, Jiangang, Yuan, Huijuan, Liu, Taiyuan, Cui, Xingwei, Tang, Zhenchao, Du, Yang, Wang, Meiyun, Lin, Yusong, Tian, Jie. Identification of Cognitive Dysfunction in Patients with T2DM Using Whole Brain Functional Connectivity. GENOMICS PROTEOMICS & BIOINFORMATICS[J]. 2019, 17(4): 441-452, http://lib.cqvip.com/Qikan/Article/Detail?id=7101029398.
[44] Wang, Shuo, Liu, Zhenyu, Rong, Yu, Zhou, Bin, Bai, Yan, Wei, Wei, Wei, Wei, Wang, Meiyun, Guo, Yingkun, Tian, Jie. Deep learning provides a new computed tomography-based prognostic biomarker for recurrence prediction in high-grade serous ovarian cancer. RADIOTHERAPY AND ONCOLOGY[J]. 2019, 132: 171-177, http://dx.doi.org/10.1016/j.radonc.2018.10.019.
[45] Wang, Shuo, Shi, Jingyun, Ye, Zhaoxiang, Dong, Di, Yu, Dongdong, Zhou, Mu, Liu, Ying, Gevaert, Olivier, Wang, Kun, Zhu, Yongbei, Zhou, Hongyu, Liu, Zhenyu, Tian, Jie. Predicting EGFR mutation status in lung adenocarcinoma on computed tomography image using deep learning. EUROPEAN RESPIRATORY JOURNAL[J]. 2019, 53(3): http://ir.ia.ac.cn/handle/173211/23571.
[46] Mo, Jiajie, Liu, Zhenyu, Sun, Kai, Ma, Yanshan, Hu, Wenhan, Zhang, Chao, Wang, Yao, Wang, Xiu, Liu, Chang, Zhao, Baotian, Zhang, Kai, Zhang, Jianguo, Tian, Jie. Automated detection of hippocampal sclerosis using clinically empirical and radiomics features. EPILEPSIA[J]. 2019, 60(12): 2519-2529, [47] Liu, Zhenyu, Wang, Shuo, Dong, Di, Wei, Jingwei, Fang, Cheng, Zhou, Xuezhi, Sun, Kai, Li, Longfei, Li, Bo, Wang, Meiyun, Tian, Jie. The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges. THERANOSTICS[J]. 2019, 9(5): 1303-1322, http://ir.ia.ac.cn/handle/173211/23573.
[48] Zhenyu Liu. Radiomics of multi-parametric MRI for pretreatment prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer: a multicenter study. Clinical Cancer Research. 2019, [49] Fan, Yanghua, Liu, Zhenyu, Hou, Bo, Li, Longfei, Liu, Xiaohai, Liu, Zehua, Wang, Renzhi, Lin, Yusong, Feng, Feng, Tian, Jie, Feng, Ming. Development and validation of an MRI-based radiomic signature for the preoperative prediction of treatment response in patients with invasive functional pituitary adenoma. EUROPEAN JOURNAL OF RADIOLOGY[J]. 2019, 121: http://dx.doi.org/10.1016/j.ejrad.2019.108647.
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[51] Zhu, Xinzhong, Dong, Di, Chen, Zhendong, Fang, Mengjie, Zhang, Liwen, Song, Jiangdian, Yu, Dongdong, Zang, Yali, Liu, Zhenyu, Shi, Jingyun, Tian, Jie. Radiomic signature as a diagnostic factor for histologic subtype classification of non-small cell lung cancer. EUROPEAN RADIOLOGY[J]. 2018, 28(7): 2772-2778, https://www.webofscience.com/wos/woscc/full-record/WOS:000434251800008.
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发表著作
(1) Targeting Mechanisms of Typical Indications of Acupuncture, Springer, 2017-08, 第 1 作者
(2) Radiomics in medical imaging—detection, extraction and segmentation, Springer, 2018-01, 第 3 作者

科研活动

   
科研项目
( 1 ) 基于影像组学的低级别胶质瘤引发癫痫风险评估方法研究, 主持, 国家级, 2018-01--2019-12
( 2 ) 基于多模态磁共振成像的糖尿病患者脑网络机制研究, 主持, 国家级, 2016-01--2018-12
( 3 ) 一体化TOF-PET-MRI 脑血流定量方法研究及在脑疾病的应用, 主持, 国家级, 2016-07--2018-12
( 4 ) 基于影像组学的局部进展期直肠癌新辅助放化疗效果评估研究, 主持, 省级, 2018-01--2020-12