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，中科院分子影像重点实验室影像组学方向负责人，中科院青年创新促进会优秀会员，北京癌症防治学会胃癌防治专委会常务委员，中国医师协会放射医师分会互联网与大数据影像专业组副组长，入选了“全国医学影像领域学者论文学术影响力排名(2012~2021) Top 100”学者，入选美国斯坦福大学团队和爱思唯尔数据库发布的全球前2%顶尖科学家榜单（World's Top 2% Scientists 2022），中国图象图形学会“青年科学家”获得者，全国胃癌学术大会“未来科学家”，国家科技部重点研发计划青年科学家项目首席科学家（诊疗装备与生物医用材料）。
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、科技部重点研发计划青年科学家项目等多项。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，近年来在医学领域主流SCI期刊Annals of Oncology (SCI IF: 50.5，2篇)，European Respiratory Journal (SCI IF: 24.3)等上发表论文100余篇，ESI Top 1%高被引论文12篇，谷歌H因子55，2篇论文入选2021年中国医学影像领域TOP100高价值论文，1篇论文获评2022 IEEE Engineering in Medicine and Biology Prize Paper Award，Web of Science检索胃癌影像组学和鼻咽癌影像组学两个方向，申请人发表的2篇论文引用次数均排名国际第一。研究连续五年（2019-2023）纳入《中国临床肿瘤学会CSCO胃癌诊疗指南》，被写入美国、日本等十余国家专家在Gut杂志上联合撰写的胃食管结合部肿瘤国际临床共识，入选基金委重大研究计划中期亮点成果，并获评为首都前沿学术成果。此外，还获四川省科技进步一等奖，获授权国家发明专利25项，申请软件著作权23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。

肿瘤影像大数据分析

[1] 国家自然科学基金 国际(地区)合作与交流项目
名称：基于群体学习的晚期鼻咽癌预后预测及治疗方案推荐
基金资助号：82361168664（2024.1.1-2026.12.31），170万
项目负责人：董迪
[2] 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（2021.1.1-2023.12.31），120万
项目负责人：董迪
[3] 国家重点研发计划——“诊疗装备与生物医用材料”重点专项 诊疗装备青年科学家项目
项目名称：基于术前与术中影像的胃癌淋巴结转移辅助诊断系统
项目负责人：董迪
总经费：200万
项目编号：2023YFC2415200（2023.11.01-2026.10.31）
[4] 国家自然科学基金面上基金项目
名称：基于可解释性影像组学的进展期胃癌双抗免疫治疗疗效预测研究
基金资助号：82372053（2024.1.1-2027.12.31），48万
项目负责人：董迪
[5] 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（2020.1.1-2023.12.31），55万
项目负责人：董迪
[6] 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（2020.1.1-2022.12.31），80万
项目负责人：董迪
项目情况：被评为中期亮点成果，结题优秀
[7] 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（2018.1.1-2021.12.31），55万
项目负责人：董迪

[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: 50.5) (ESI Highly Cited Paper)
[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: 50.5) (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: 9.3)
[4] Ting Liu#, Di Dong#, Xun Zhao#, Xiaomin Ou#, Junlin Yi#, Jian Guan#, Ye Zhang, Lv Xiaofei, Chuanmiao Xie, Donghua Luo, Rui Sun, Qiuyan Chen, Lv Xing, Shanshan Guo, Liting Liu, Dafeng Lin, Yanzhou Chen, Jieyi Lin, Meijuan Luo, Wenbin Yan, Meilin He, Mengyuan Mao, Manyi Zhu, Wenhui Chen, Bowen Shen, Shiqian Wang, Hailin Li, Lianzhen Zhong, Chaosu Hu, Dehua Wu, Haiqiang Mai*, Jie Tian*, Linquan Tang*. Radiomic signatures reveal multiscale intratumor heterogeneity associated with tissue tolerance and survival in re-irradiated nasopharyngeal carcinoma: a multicenter study. BMC Medicine, 2023, 21(1): 464. Published: 27 November 2023. DOI: 10.1186/s12916-023-03164-3 (SCI IF: 9.3)
[5] 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 (SCI IF: 17.6) (ESI Highly Cited Paper) (TOP100 high-value papers in the field of medical imaging in China in 2021) (Popular paper in IEEE Reviews in Biomedical Engineering)
[6] Zipei Wang#, Mengjie Fang#, Jie Zhang#, Linquan Tang#, Lianzhen Zhong, Hailin Li, Runnan Cao, Xun Zhao, Shengyuan Liu, Ruofan Zhang, Xuebin Xie*, Haiqiang Mai, Sufang Qiu, Jie Tian*, Di Dong*, Radiomics and Deep Learning in Nasopharyngeal Carcinoma: A Review, IEEE Reviews in Biomedical Engineering, 2023, 17: 118-135. Publication: 25 April 2023. DOI: 10.1109/RBME.2023.3269776. (SCI IF: 17.6)
[7] 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: 24.3) (ESI Highly Cited Paper)
[8] 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: 11.5) (ESI Highly Cited Paper)
[9] 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: 11.5)
[10] 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: 11.5) (ESI Highly Cited Paper)
[11] Yujia Liu#, Hui Duan#, Di Dong#, Jiaming Chen#, Lianzhen Zhong, Liwen Zhang, Runnan Cao, Huijian Fan, Zhumei Cui, Ping Liu, Shan Kang, Xuemei Zhan, Shaoguang Wang, Xun Zhao, Chunlin Chen*, Jie Tian*, Development of a deep learning-based nomogram for predicting lymph node metastasis in cervical cancer: a multicenter study, Clinical and Translational Medicine, 2022,12: e938. First published: 15 July 2022. DOI: 10.1002/ctm2.938 (SCI IF: 10.6)
[12] 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: 10.9) (ESI Highly Cited Paper)
[13] 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(2): e000550. Published: July 6, 2020. DOI: 10.1136/jitc-2020-000550 (SCI IF: 10.9)
[14] Bingxi He#, Yu Guo#, Yongbei Zhu#, Lixia Tong, Boyu Kong, Kun Wang, Caixia Sun, Hailin Li, Feng Huang, Liwei Wu, Meng Wang, Fanyang Meng, Le Dou, Kai Sun, Tong Tong, Zhenyu Liu, Ziqi Wei, Wei Mu, Shuo Wang, Zhenchao Tang, Shuaitong Zhang, Jingwei Wei, Lizhi Shao, Mengjie Fang, Juntao Li, Shouping Zhu, Lili Zhou, Shuo Wang, Di Dong*, Huimao Zhang*, Jie Tian*, From signal to knowledge: The diagnostic value of raw data in artificial intelligence prediction of human data for the first time, Engineering, 2023 in press. Available online 22 April 2023. DOI: 10.1016/j.eng.2023.02.013 (SCI IF: 12.8)
[15] 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: 12.4)
[16] 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: 12.4) (ESI Highly Cited Paper)
[17] 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: 7.7)
[18] Xun Zhao#, Yujing Liang#, Xu Zhang#, Dongxiang Wen#, Wei Fan#, Linquan Tang*, Di Dong*, Jie Tian*, Haiqiang Mai*, Deep learning signatures reveal multiscale intratumor heterogeneity associated with biological functions and survival in recurrent nasopharyngeal carcinoma, European Journal of Nuclear Medicine and Molecular Imaging, 2022, 49: 2972-2982. Published online: 26 April 2022. DOI: 10.1007/s00259-022-05793-x (SCI IF: 9.1)
[19] Liwen Zhang#, Di Dong#, Yongqing Sun#, Chaoen Hu, Congxin Sun#, Qingqing Wu*, Jie Tian*, Development and validation of a deep learning model to screen for trisomy 21 during the first trimester from nuchal ultrasonographic images, JAMA Network Open, 2022, 5(6): e2217854. Published: June 21, 2022. DOI: 10.1001/jamanetworkopen.2022.17854 (SCI IF: 13.8)
[20] Hailin Li, Siwen Wang, Bo Liu, Mengjie Fang, Runnan Cao, Bingxi He, Shengyuan Liu, Chaoen Hu, Di Dong*, Ximing Wang*, Hexiang Wang*, Jie Tian*, A Multi-View Co-Training Network for Semi-Supervised Medical Image-Based Prognostic Prediction, Neural Networks 2023, 164: 455-463. Available online: April 24, 2023. DOI: 10.1016/j.neunet.2023.04.030 (SCI IF: 7.8)

[1] 董迪入选全球前2%顶尖科学家榜单(World's Top 2% Scientists 2022)。
[2] 董迪获2022年中国图象图形学学会（CSIG）青年科学家奖。
[3] 董迪获2022年第十七届胃癌全国学术会议“未来科学家”二等奖。
[4] 董迪入选 “全国医学影像领域学者论文学术影响力排名(2012~2021) Top 100”学者

[1] 田捷，董迪，巩立鑫，胡朝恩，杨鑫，操润楠，基于修复和选择性增强的胃镜图像分析系统、方法及设备，专利号：ZL202110517412.2，授权日期：2023.04.07，申请日：2021.05.12，公开(公告)号：CN113256572A，公开日期：2021.08.13。
[2] 田捷，董迪，钟连珍，胡朝恩，杨鑫，赵洵，融合多示例学习和多任务深度影像组学的生存期分析系统，专利号：ZL202110393908.3，授权日期：2023.6.27，申请日：2021.4.13，公开(公告)号：CN112927799A，公开日期：2021.6.8
[3] 田捷，董迪，王思雯，胡振华，胡朝恩，杨鑫，基于分布式深度学习的医学影像智能分析系统，专利号：ZL202110268700.9，授权日期：2023.9.19，申请日：2021.03.12，公开(公告)号：CN112988382A，公开日期：2021.6.18
[4] 田捷，董迪，李聪，胡振华，杨鑫，胡朝恩，基于Unet迁移学习的胃印戒细胞癌图像智能分类系统，专利号：ZL202110270657.X，授权日期：2023.4.28，申请日：2021.03.12，公开(公告)号：CN 112861994A, 公开日期：2021.05.28
[5] 田捷，董迪，李海林，胡振华，王思雯，胡朝恩，基于深度学习的淋巴结转移影像分析系统、方法及设备，专利号：ZL202110272069.X，授权日期：2023.4.7，申请日：2021.3.12，公开日期：2021.6.18