牟玮

教授

教授  博士生导师   硕士生导师 

电子邮箱:

入职时间:2022-03-03

所在单位:医学科学与工程学院

学历:博士研究生

办公地点:办公楼五号楼416

在职信息:在职

个人简介

牟玮,国家自然科学基金优青,入选2023全球前2%顶尖科学家榜单,多年来一直从事医学影像与人工智能交叉学科研究,围绕肺癌、宫颈癌和胶质瘤等癌症的诊疗决策,在PET/CT,MRI等多模态影像分析方面开展了深入的医工交叉研究。以第一作者在Nature Communications,  Journal for Immunotherapy of Cancer,  Cancer Reserach、European Journal of Nuclear Medicine等信息与医学领域权威期刊发表论文20余篇。主持并参与国自然优秀青年、面上项目、北自然重点、科技部国家重点研发计划等,获美国国家癌症研究所青年学者奖等多项国际奖项,任中国康复技术转化及发展促进会精准医疗与肿瘤康复专业委员会常务委员、中华医学会核医学分会大数据与人工智能工作委员会副组长等。


教育经历

2011.09 - 2016.07   中国科学院自动化研究所,模式识别与智能系统,工学博士

2007.09 - 2011.07   华中科技大学控制科学与工程系,测控技术与仪器,工学学士


工作经历

2023.01 - 至今         北京航空航天大学, 医学科学与工程学院, 教授

2022.03 - 2022.12   北京航空航天大学, 医学科学与工程学院, 副教授

2020.12 - 2021.07   美国墨菲特癌症研究中心,研究员

2016.12 - 2020.12   美国墨菲特癌症研究中心,博士后


研究方向

多模态医学图像分析、人工智能、模式识别、深度学习等多学科交叉


科研项目

[1]  国家自然科学基金委员会, 优秀青年科学基金项目, 肺癌多模态医学影像分析, 2023-01-01 至 2025-12-31, 200万元, 在研, 主持

[2] 国家自然科学基金委员会, 面上项目, 62176013, 基于PET/CT解析多分子标志物与临床事件的晚期肺癌免疫治疗预后评估, 2022-01-01 至 2025-12-31, 53万元, 在研, 主持

[3] 科技部国家重点研发计划,多癌联筛早诊新体系的建立和全国推广应用新策略的评价,2022.11-2025.12, 3000万元,课题骨干(承担经费115万元)

[4] 北京市自然科学基金委员会, 北京市自然科学基金-海淀原始创新联合基金重点项目, 基于多组学的多维立体肺癌早期筛查体系建立及应用研究, 2023-01-01 至 2025-12-31, 100万元, 子课题负责人(承担经费15万元)

[5] National Institutes of Health, RO1, CA143062-02, Radiomics of NSCLC, 2016-12 至 2020-12, 340.35万美元, 结题, 课题骨干


招生信息

欢迎具有人工智能影像分析/柔性电子/硬件系统搭建背景的学子加入本研究团队一起从事研究工作。

计划招博士后1-2名(高薪招聘,长期有效),每年计划招收博士研究生2名,硕士研究生1名。



代表性论著

(1) Wei Mu; Lei Jiang; Jianyuan Zhang; Yu Shi; Jhanelle E Gray; Ilke Tunali; Chao Gao; Yingyi ng Sun; Jie Tian; Xinming Zhao; Xilin Sun; Robert J Gillies; Matthew B Schabath ; Non-invasive decision support for NSCLC treatment using PET/CT Radiomics, Nature Communications, 2020, 11: 5228  (SCI IF: 14.919) 

(2) Wei Mu; Ilke Tunali; Jhanelle E. Gray; Jin Qi; Matthew B. Schabath; Robert J. Gillies ; Radiomics of 18F-FDG PET/CT images predicts clinical benefit of advanced NSCLC patients to checkpoint blockade immunotherapy, European Journal of Nuclear Medicine and Molecular Imaging, 2020, 47(5): 1168-1182 (SCI IF: 9.236) 

(3) Wei Mu; Lei Jiang; Yu Shi; Ilke Tunali; Jhanelle E. Gray; Evangelia Katsoulakis; Jie Tian; Robert J. Gillies; Matthew B. Schabath ; Non-invasive measurement of PD-L1 status and prediction of immunotherapy response using deep learning of PET/CT images, Journal for ImmunoTherapy of Cancer, 2021, 9(6): e002118 (SCI IF: 13.751) 

(4) Wei Mu; Matthew B. Schabath; Robert J. Gillies; Images are Data: Challenges and opportunities in the clinical translation of Radiomics, Cancer Research, 2022  (SCI IF: 12.701) 

(5) Wei Mu; Evangelia Katsoulakis; Christopher J. Whelan; Kenneth L. Gage; Matthew B. Schabath; Robert J. Gillies ; Radiomics predicts risk of cachexia in advanced NSCLC patients treated with immune checkpoint inhibitors, British Journal of Cancer, 2021, 125: 229-239 (SCI IF: 7.64) 

(6) Wei Mu; Ilke Tunali; Jin Qi; Matthew B. Schabath; Robert James Gillies ; Radiomics of 18F-Fluorodeoxyglucose PET/CT Images Predicts Severe Immune-related Adverse Events in Patients with NSCLC, Radiology: Artificial Intelligence, 2020, 2(1): e190063 

(7) Wei Mu; Chang Liu; Feng Gao; Yafei Qi; Hong Lu; Zaiyi Liu; Xianyi Zhang; Xiaoli Cai; Ruo Yun Ji; Yang Hou; Jie Tian; Yu Shi ; Prediction of clinically relevant Pancreatico-enteric Anastomotic Fistulas after Pancreatoduodenectomy using deep learning of Preoperative Computed Tomography, Theranostics, 2020, 10(21): 9779-9788 (SCI IF: 11.556) (SCI IF: 11.556) 

(8) Wei Mu; Ying Liang; Lawrence O Hall; Yan Tan; Yoganand Balagurunathan; Robert Wenham; Ning Wu; Jie Tian; Robert J. Gillies ; 18F-PET/CT habitat radiomics predicts outcome of cervical cancer patients treated with chemoradiotherapy, Radiology: Artificial Intelligence, 2020, 2(6): e190218 

(9) Wei Mu; Zhe Chen; Xiaoqian Dai; Jie Tian ; Noninvasive Estimation of the Input Function for Dynamic Mouse F-18-FDG MicroPET Studies, IEEE Transactions on Biomedical Engineering, 2013, 60(11): 3103-3112 (SCI IF: 4.538)

(10) Wei Mu; Zhe Chen; Wei Shen; Feng Yang; Ying Liang; Ruwei Dai; Ning Wu; Jie Tian ; A Segmentation Algorithm for Quantitative Analysis of Heterogeneous Tumors of the Cervix With F-18-FDG PET/CT, IEEE Transactions on Biomedical Engineering, 2015, 62(10): 2465-2479 (SCI IF: 4.538)

(11) Wei Mu; Zhe Chen; Ying Liang; Wei Shen; Feng Yang; Ruwei Dai; Ning Wu; Jie Tian ; Staging of cervical cancer based on tumor heterogeneity characterized by texture features on F-18-FDG PET images, Physics in Medicine and Biology, 2015, 60(13): 5123-5139  (SCI IF: 3.609) 

(12) Fei Kang#; Wei Mu#; Jie Gong#; Shengjun Wang; Guoquan Li; Guiyu Li; Wei Qin; Jie Tian; Jing Wang ; Integrating manual diagnosis into radiomics for reducing the false positive rate of 18F-FDG PET/CT diagnosis in patients with suspected lung cancer, European journal of medicine and molecular imaging, 2019, 46(13): 2770-2779 (SCI IF: 9.236) 

(13) Bruna V. Jardim-Perassi#; Wei Mu#; Suning Huang; Michal R. Tomaszewski; Jan Poleszczuk; Mahmoud A. Abdalah; Mikalai M. Budzevich; William Dominguez-Viqueira; Damon R. Reed; Marilyn M. Bui; Joseph O. Johnson; Gary V. Martinez; Robert J. Gillies ; Deep-learning and MR images to target hypoxic habitats with evofosfamide in preclinical models of sarcoma, Theranostics, 2021, 11(11): 5313-5329 (SCI IF: 11.556) 

(14) Sandy Napel; Wei Mu; Bruna V. Jardim‐Perassi; Hugo J. W. L. Aerts; Robert J. Gillies ; Quantitative imaging of cancer in the postgenomic era: Radio(geno)mics, deep learning, and habitats, Cancer, 2018, 124(24): 4633-4649 (SCI IF: 6.86) 

(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 (SCI IF: 11.556) 


学术奖励

(1) Wei Mu; Laurence P. Clarke Young Scientist Award, The Quantitative Imaging Network o f the National Cancer Institute, National Institutes of Health, 2021

(2) Wei Mu; Young Investigator of the Year Runner-Up Award, World Molecular Imaging Congress,  2020

(3) Wei Mu; Women in Molecular Imaging Network Scholar Award, World Molecular Imaging Congress,  2020


特邀报告

(1) Wei Mu; Radiomics and AI-based treatment decision support for non-small cell lung cancer (invited talk), AACR Virtual Special Conference: Artificial Intelligence, Diagnosis, and Imaging, Virtual meeting, United States, 2021-1-13至2021-1-14 

(2) Wei Mu ; Radiomics and AI-based treatment decision support for non-small cell lung cancer (invited talk), Quantitative Imaging Network Annual Meeting, Virtual meeting, United States, 2021-1-22至2021-1-22