研究领域        模式识别与智能系统——医学影像大数据分析与处理

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简历
董迪，工学博士，基金委优青，中国科学院自动化研究所研究员，博士生研究生导师，中国科学院分子影像重点实验室影像组学方向责任老师，中国科学院青年创新促进会会员，北京癌症防治学会胃癌防治专业委员会常务委员，研究型医院学会放射专业青年委员会委员，中国抗癌协会肿瘤人工智能专业委员会委员，中国体视学会会员，中国生物物理学会分子影像学专委会委员，AACR active member，ESR corresponding member。在肿瘤影像组学和医学影像大数据智能分析等方面开展了长期的研究工作，提高了影像辅助肿瘤诊疗的效果，获四川省科技进步一等奖，研究连续两年（2019-2020）纳入《中国临床肿瘤学会CSCO胃癌诊疗指南》。牵头主持国家基金委优秀青年基金项目、国家基金委重大研究计划培育项目、国家基金委面上基金项目（2项）、国家基金委青年基金项目、科技部重点研发计划子课题等多项。牵头联合50余家三甲医院建立万余例癌症影像组学数据库，研发的预测软件在百余家医院推广。近年来在医学领域主流SCI期刊Annals of Oncology (SCI IF: 32.976，2篇)，European Respiratory Journal (SCI IF: 16.671)，Clinical Cancer Research (SCI IF: 12.531，3篇)，BMC Medicine (SCI IF: 8.775)等上发表论文60余篇，ESI Top 1%高被引论文10篇，SCI IF>10论文9篇，谷歌H因子34，获授权国家发明专利25项，申请软件著作权22项。多次在影像组学会议、北美放射年会、世界分子影像会议、国际生物医学工程会议等国际主流会议上做口头报告。担任IEEE TMI、European Radiology、Ebiomedicine等杂志的审稿人。

欢迎临床医生和工科师生来中科院分子影像重点实验室访问交流，邮箱：di.dong@ia.ac.cn

 

教育经历

2008/9 - 2013/7，中国科学院大学，模式识别与智能系统，博士（保送硕博连读），导师：田捷

2004/9 - 2008/7，北京科技大学，自动化，学士

 

工作情况

2013/7-2015/10     中国科学院自动化研究所, 助理研究员

2015/10-2020/10  中国科学院自动化研究所, 副研究员

2020/10-至今         中国科学院自动化研究所, 研究员

2017/01-2021/07   中国科学院自动化研究所, 硕士研究生导师

2021/07-至今         中国科学院自动化研究所, 博士研究生导师

学术任职

2021/6-至今 国家癌症中心“中国居民癌症防控行动”项目组专家

2020/10/24-至今 北京癌症防治学会胃癌防治专业委员会，常务委员

2019/8/16-至今  中国抗癌协会肿瘤人工智能专业委员会，专业委员

2020/11/24-至今  中国抗癌协会鼻咽癌专业委员会，专业委员

2020/11/24-至今  中国抗癌协会胃癌专业委员会，专业委员

2016/11/17- 2019/11/17 中国研究型医院学会放射学专业委员会，青年委员

 

学术成就 

以第一或通讯作者（含共同）发表SCI论文60余篇，部分代表性论文如下:

[1]     Di Dong#, Mengjie Fang#, Lei Tang#, Xiuhong Shan#, Jianbo Gao#, Francesco Giganti#, Rongpin Wang, Xin Chen, Xiaoxiao Wang, Diego Palumbo, Jia Fu, Wuchao Li, Jing Li, Lianzhen Zhong, Francesco De Cobelli, Jiafu Ji*, Zaiyi Liu*, Jie Tian*, Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: an international multicenter study, Annals of Oncology, 2020, 31(7): 912-920. Published: April 15, 2020. DOI: 10.1016/j.annonc.2020.04.003 (SCI IF: 32.976)

[2]     Di Dong#, Lei Tang#, Ziyu Li#, Mengjie Fang#, Jianbo Gao#, Xiuhong Shan#, Xiangji Ying, Yingshi Sun, Jia Fu, Xiaoxiao Wang, Liming Li, Zhenhui Li, Dafu Zhang, Yan Zhang, Zhemin Li, Fei Shan, Zhaode Bu, Jie Tian*, Jiafu Ji*, Development and validation of an individualized nomogram to identify occult peritoneal metastasis in patients with advanced gastric cancer, Annals of Oncology, 2019, 30(3): 431-438. Published: March 01, 2019. DOI: 10.1093/annonc/mdz001 (SCI IF: 32.976) (ESI Highly Cited Paper)

[3]     Di Dong#, Fan Zhang#, Lianzhen Zhong#, Mengjie Fang, Chenglong Huang, Jijin Yao, Ying Sun, Jie Tian*, Jun Ma*, Linglong Tang*, Development and validation of a novel MR imaging predictor of response to induction chemotherapy in locoregionally advanced nasopharyngeal cancer: a randomized controlled trial substudy (NCT01245959), BMC Medicine, 2019, 17(1): 190. Published: October 23, 2019. DOI: 10.1186/s12916-019-1422-6 (SCI IF: 8.775)

[4]     Di Dong#, Zhenchao Tang#, Shuo Wang#, Hui Hui#, Lixin Gong#, Yao Lu#, Zhong Xue, Hongen Liao, Fang Chen, Fan Yang, Ronghua Jin, Kun Wang, Zhenyu Liu, Jingwei Wei, Wei Mu, Hui Zhang, Jingying Jiang, Jie Tian*, Hongjun Li*, The role of imaging in the detection and management of COVID-19: a review, IEEE Reviews in Biomedical Engineering, 2020,14:16-29. Published: 27 April 2020. DOI: 10.1109/RBME.2020.2990959

[5]     Shuo Wang#, Jingyun Shi#, Zhaoxiang Ye#, Di Dong#, Dongdong Yu#, Mu Zhou#, Ying Liu, Olivier Gevaert, Kun Wang, Yongbei Zhu, Hongyu Zhou, Zhenyu Liu, Jie Tian*, Predicting EGFR mutation status in lung adenocarcinoma on computed tomography image using deep learning, European Respiratory Journal, 2019, 53(3): 1800986. Published online: March 28, 2019. DOI: 10.1183/13993003.00986-2018 (SCI IF: 16.671) (ESI Highly Cited Paper)

[6]     Hao Peng#, Di Dong#, Mengjie Fang#, Lu Li#, Linglong Tang, Lei Chen, Wenfei Li, Yanping Mao, Wei Fan, Lizhi Liu, Li Tian, Aihua Lin, Ying Sun, Jie Tian*, Jun Ma*, Prognostic value of deep learning PET/CT-based radiomics: potential role for future individual induction chemotherapy in advanced nasopharyngeal carcinoma, Clinical Cancer Research, 2019, 25(14): 4271-4279. Published: July 2019. DOI: 10.1158/1078-0432.CCR-18-3065 (SCI IF: 12.531) (ESI Highly Cited Paper)

[7]     Jiangdian Song#, Jingyun Shi#, Di Dong#, Mengjie Fang, Wenzhao Zhong, Kun Wang, Ning Wu, Yanqi Huang, Zhenyu Liu, Yue Cheng, Yuncui Gan, Yongzhao Zhou, Ping Zhou, Bojiang Chen, Changhong Liang, Zaiyi Liu*, Weimin Li*, Jie Tian*, A new approach to predict progression-free survival in stage IV EGFR-mutant NSCLC patients with EGFR-TKI therapy, Clinical Cancer Research, 2018, 24(15): 3583-3592. Published: August 2018. DOI: 10.1158/1078-0432.CCR-17-2507 (SCI IF: 12.531)

[8]     Bin Zhang#, Jie Tian#, Di Dong#, Dongsheng Gu, Yuhao Dong, Lu Zhang, Zhouyang Lian, Jing Liu, Xiaoning Luo, Shufang Pei, Xiaokai Mo, Wenhui Huang, Fusheng Ouyang, Baoliang Guo, Long Liang, Wenbo Chen, Changhong Liang, Shuixing Zhang*, Radiomics features of multiparametric MRI as novel prognostic factors in advanced nasopharyngeal carcinoma, Clinical Cancer Research, 2017, 23(15): 4259-4269. Published: August 2017. DOI: 10.1158/1078-0432.CCR-16-2910 (SCI IF: 12.531) (ESI Highly Cited Paper)

[9]     Shuo Wang#, Mu Zhou#, Zaiyi Liu, Zhenyu Liu, Dongsheng Gu, Yali Zang, Di Dong#, Olivier Gevaert#, Jie Tian*, Central focused convolutional neural networks: developing a data-driven model for lung nodule segmentation, Medical Image Analysis, 2017, 40: 172–183. Published: August 2017. DOI: 10.1016/j.media.2017.06.014 (SCI IF: 8.545) (ESI Highly Cited Paper)

[10] Bingxi He#, Di Dong#, Yunlang She#, Caicun Zhou, Mengjie Fang, Yongbei Zhu, Henghui Zhang, Zhipei Huang*, Tao Jiang*, Jie Tian*, Chang Chen*, Predicting response to immunotherapy in advanced non-small cell lung cancer using tumour mutational burden radiomic biomarker, Journal for ImmunoTherapy of Cancer, 2020, 8: e000550. Published: July 6, 2020. DOI: 10.1136/jitc-2020-000550 (SCI IF: 13.751)

[11] Panwen Tian#, Bingxi He#, Wei Mu#, Kunqin Liu, Li Liu, Hao Zeng, Yujie Liu, Lili Jiang, Ping Zhou, Zhipei Huang*, Di Dong*, Weimin Li*, Assessing PD-L1 expression in non-small cell lung cancer and predicting responses to immune checkpoint inhibitors using deep learning on computed tomography images, Theranostics, 2021, 11(5): 2098-2107. Published: 2021-1-1. doi: 10.7150/thno.48027(SCI IF: 11.556)

[12] Zhenyu Liu#, Shuo Wang#, Di Dong#, Jingwei Wei#, Cheng Fang#, Xuezhi Zhou, Kai Sun, Longfei Li, Bo Li*, Meiyun Wang*, Jie Tian*, The applications of radiomics in precision diagnosis and treatment of oncology: opportunities and challenges, Theranostics, 2019, 9(5): 1303–1322. Published: 2019-2-12. DOI: 10.7150/thno.30309 (SCI IF: 11.556) (ESI Highly Cited Paper)

[13] Hao Hu#, Lixin Gong#, Di Dong#, Liang Zhu, Min Wang, Jie He, Lei Shu, Yiling Cai, Shilun Cai, Wei Su, Yunshi Zhong, Cong Li, Yongbei Zhu, Mengjie Fang, Lianzhen Zhong, Xin Yang, Pinghong Zhou*, Jie Tian*, Identifying early gastric cancer under magnifying narrow-band images with deep learning: a multicenter study, Gastrointestinal Endoscopy, 2021, 93(6): 1333-1341.e3. Published: November 25, 2020. DOI: 10.1016/j.gie.2020.11.014 (SCI IF: 9.427)

在研课题

[1]     国家自然科学基金 优秀青年科学基金项目

名称：胃癌影像组学

基金资助号：82022036，120万

项目负责人：董迪

[2]    国家自然科学基金 重大研究计划培育项目

名称：基于影像和病理融合的胃肠道肿瘤微卫星不稳定（MSI）评估及免疫治疗疗效预测

基金资助号：91959130，80万

项目负责人：董迪

[3]    国家自然科学基金面上基金项目

名称：基于多模态影像组学的胃癌新辅助化疗疗效预测研究

基金资助号：81971776，55万

项目负责人：董迪

[4]    国家自然科学基金面上基金项目

名称：基于影像组学的EGFR突变型晚期非小细胞肺癌靶向治疗疗效预测研究

基金资助号：81771924，55万

项目负责人：董迪

[5]    中国科学院项目

名称：青年创新促进会2017

项目资助号：Y7S7031X51，80万

项目负责人：董迪

[6]    国家重点研发计划——“重大慢性非传染性疾病防控研究”重点专项

项目名称：肺癌筛查和干预技术及方案研究

子课题名称：基于影像组学和大数据的肺癌筛查新技术研究

子课题负责人：董迪

子课题编号：2017YFC1308701，284万元