D. Dong#, L. Tang#, Z.-Y. Li#, M.-J. Fang#, J.-B. Gao#, X.-H. Shan#, X.-J. Ying, Y.-S. Sun, J. Fu, X.-X. Wang, L.-M. Li, Z.-H. Li7, D.-F. Zhang, Y. Zhang, Z.-M. Li, F. Shan, Z.-D. Bu, J. Tian, J.-F. Ji*. Development and validation of an individualized nomogram to identify occult peritoneal metastasis in patients with advanced gastric cancer,Annals of Oncology ,doi:10.1093/annonc/mdz001 (Published online 23 January 2019)

Tang L#, Wang XJ#, Baba H, Giganti F. Gastric cancer and image-derived quantitative parameters: Part 2-a critical review of DCE-MRI and 18F-FDG PET/CT findings.,Eur Radiol,

Sun RJ#; Fang MJ#; Tang L#; Li XT; Lu QY; Dong D; Tian J; Sun YS. CT-based deep learning radiomics analysis for evaluation of serosa invasion in advanced gastric cancer.,Eur J Radiol.,

Xing Wang#, Li Zhang#, Xin Yang#, Lei Tang#, Jie Zhao, Gaoxiang Chen, Xiang Li , Shi Yan , Shaolei Li , Yue Yang , Yue Kang , Quanzheng Li, Nan Wu. Deep learning combined with radiomics may optimize the prediction in differentiating high-grade lung adenocarcinomas in ground glass opacity lesions on CT scans.,Eur J Radiol.,

Li ZY#, Tang L#, Li ZM#, Li YL#, Fu J, Zhang Y, Li XT, Ying XJ, Ji JF. Four-Point Computed Tomography Scores for Evaluation of Occult Peritoneal Metastasis in Patients with Gastric Cancer: A Region-to-Region Comparison with Staging Laparoscopy.,Ann Surg Oncol,

Fu J, Fang MJ, Dong D, Li J, Sun YS, Tian J, Tang L*. Heterogeneity of metastatic gastrointestinal stromal tumor on texture analysis: DWI texture as potential biomarker of overall survival.,Eur J Radiol,

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.,Ann Oncol,

Jia Fu, Lei Tang*, Zi-Yu Li, Xiao-Ting Li, Hai-Feng Zhu, Ying-Shi Sun, Jia-Fu Ji. Diffusion kurtosis imaging in the prediction of poor responses of locally advanced gastric cancer to neoadjuvant chemotherapy.,Eur J Radiol,

Karaman MM#, Tang L#, Li Z, Sun Y, Li JZ, Zhou XJ*. In vivo assessment of Lauren classification for gastric adenocarcinoma using diffusion MRI with a fractional order calculus model.,Eur Radiol,

Jiazheng Li, Lei Tang*. Radiomics in Antineoplastic Agents Development: Application and Challenge in Response Evaluation.,Chin Med Sci J.,

3T 磁共振扩散成像非高斯模型早期预测胃肠道恶性肿瘤新 辅助治疗疗效, 课题负责人, 2014.1.1～2017.12.31, 国家自然科学基金面上项目（81371715）

影像学多模态成像早期预测胃肠间质瘤靶向治疗疗效, 课题负责人, 2016.6.1～2019.6.30, 北京市科委首都特色项目Z161100000516060

图像处理中的数据驱动建模和在胃癌新辅助化疗疗效预测中的应用, 课题负责人, 2018.12.1～2022.12.1, 北京市自然科学基金委员会

基于分子影像和影像组学的乳腺癌早诊、疗效评价与预后预测新技术研发(子课题), 子课题负责人, 2017.7.1～2020.12.1, 中华人民共和国科学技术部，国家重点研发计划

基于磁共振时间-空间异质性参数的多模态影像组学模型预测胃癌免疫治疗疗效., 课题负责人, 2021.1.1～2022.12.1, 北大百度基金

多模态跨尺度生物医学成像国家重大科技基础设施装置, 子课题负责人, 2019.6.10～2024.6.7, 国家重大科技基础设施建设“十三五”规划

研究生招生计划

招生年度	招生专业	学位级别	学位类型	研究方向	选拔方式
2023	放射影像学	硕士	专业学位	临床技能训练与研究	全国统考
2023	影像医学与核医学	博士	科学学位	胃肠道肿瘤影像学新技术探索	申请考核制