魏靖伟，女，中国科学院分子影像重点实验室，副研究员，硕士生导师。任中国人工智能学会智能光学成像专委会委员、海峡两岸医药卫生交流协会肿瘤学分会青年副主任委员、iLiver/Radiology Science/VCIBA期刊编委、IEEE JBHI/Digestive Liver Disease/Advanced Science等SCI期刊审稿人。主持国家自然科学基金青年项目1项，参与科技部重点研发计划、国自然重大和重点项目等项目11项。
主要研究方向为基于医学大数据的影像组学和多组学研究，通过量化包含海量信息的医学影像，以实现对肝癌分子生物学特性的精准刻画；并借助人工智能技术进行知识挖掘，进而实现对肝癌临床瓶颈问题的突破。在影像组学方法研究方面，主要工作包括具有肝癌特异性的多模态影像组学特征设计、基于小样本的传统模识分类器设计，以及基于深度学习的可视化算法设计。在临床应用方面，主要工作集中于肝癌微血管侵犯的术前多模态影像评估及多组学机制挖掘、肝癌治疗疗效评估与预后预测，以及乙肝肝硬化转化为肝癌高危人群筛选等。
围绕以肝癌关键病理/分子标志物术前精准诊断这一临床任务，通过设计具有肝癌特异性的专家语义特征库、基于多栖息地区域的特征融合算法和基于特征集合排序的特征筛选算法，实现了对肝癌影像表型的深度挖掘和准确刻画，完成肝癌术前无创智能诊断这一任务的实现。相关成果以第一作者（含共同）发表于影像分析领域主流期刊《European Radiology》（SCI IF: 7.034）和《Journal of Magnetic Resonance Imaging》（SCI IF: 5.119），以及肝癌领域主流期刊《Liver Cancer》（SCI IF: 12.430），累计引用200余次。此外，相关肝癌影像组学优化算法被作为标准分析流程写入Elsevier出版的MCCAI（医学影像计算领域顶会）系列著作《Radiomics and Its Clinical Application: Artificial Intelligence and Medical Big Data》。围绕肝癌精准外科切除方案辅助决策这一临床任务，提出了深度学习框架下基于全局注意力机制和连续梯度标签的可视化算法，有效实现了对肝癌复发高危区域的准确检测及预警；同时，搭建了原型试验系统，集成临床数据管理和治疗方案辅助决策分析模块，完成肝癌智能辅助决策系统研发这一任务的实现。相关成果以第一作者发表系列SCI文章于生物信息领域主流期刊《Cancers》（SCI IF: 6.575）和国际肝病研究协会会刊《Liver International》（SCI IF: 8.754，医学一区，封面文章）。综上，聚焦于肝癌影像组学，开展了肝癌影像特征工程算法优化及术前可视化算法研发的系列研究工作，积累了多年多源异构临床数据的智能融合分析方法，并具备研发基于多尺度、多模态数据的智能诊断和预后预测原型试验系统的丰富经验。
基于上述研究基础，在生物医学工程、医学影像定量分析及肝癌临床领域已发表SCI论文共计30余篇，其中，近三年以第一作者（含共同）发表SCI论文共计20篇，总影响因子>130分，总引用次数2087次，H-index: 21。以第一作者和通讯作者（含共同）发表IEEE及光学工程类会议论文3篇，肝癌领域国际会议文章9篇。此外，作为主要作者发表Elsevier出版MICCAI（医学影像计算领域顶会）系列著作1部和Springer出版的智能系统系列著作/章节1部。
智能生物医学影像
图像处理与分析
影像组学及多组学
1. 国家自然科学基金青年项目（82001917）：基于深度学习影像组学的肝细胞癌微血管侵犯预测研究
2. 国家自然科学基金重点项目（子课题，81930053）：多模态深度学习网络构建用于术前预测肝癌微血管侵犯
3. 国家自然科学基金重大项目（子课题，82090052）：肝癌智能化精准外科的共性关键技术体系的建立
4. 科技部国家重点研发计划项目（子课题，2021YFC2500402）：常见恶性肿瘤多维度早诊精准成像技术的研发
5. 国家自然科学基金重大研究计划重点项目（子课题，92159202）：肝癌肝移植诊疗关键分子智能可视化研究
6. 科技部国家重点研发计划项目（子课题，2022YFC2503705）：消化系统恶性肿瘤(肝、胰及结直肠癌)大分割精准放疗(HFRT)关键技术研究及体系建立
7. 国家自然科学基金重点项目（子课题，U22A2023）：融合超声影像组学和lncRNA转录组学多维信息辅助中晚期肝癌精准诊疗的方法研究
8. 国家自然科学基金重点项目（子课题，U22A20343）：多维组学和病理特征交互的肝细胞癌影像预后分型关键问题研究
9. 国家自然科学基金面上项目（子课题，82172039）：基于多模态影像组学和液态活检多组学的肝门胆管癌人工智能辅助HAIC疗效预测和评效模型研究
10. 首都卫生发展科研专项项目（子课题，2020-2-1073）：基于深度学习影像组学方法的脑膜瘤病理分级及增值指数预测研究
11. 广州市重点领域研发计划项目（子课题，SL2022B03J01312）：靶向FABP4的载药纳米成像探针在胆管癌淋巴结转移的诊断与治疗中的应用研究
(1) Jingwei Wei#, Qian Ji#, Yu Gao#, Xiaozhen Yang#, Donghui Guo#, Dongsheng Gu, Chunwang Yuan*, Jie Tian*, Dawei Ding*. A multi‐scale, multi‐region and attention mechanism‐based deep learning framework for prediction of grading in hepatocellular carcinoma. Medical Physics, 2023, 50(4): 2290-2302.
(2) Jingwei Wei#, Hanyu Jiang, Yu Zhou, Jie Tian, Felipe S. Furtado, Onofrio A. Catalano*. Radiomics: A radiological evidence-based artificial intelligence technique to facilitate personalized precision medicine in hepatocellular carcinoma. Digestive and Liver Disease, 2023, 55(7): 833-847.
(3) Jingwei Wei#, Sirui Fu#, Jie Zhang#, Dongsheng Gu#, Xiaoqun Li, Xudong Chen, Shuaitong Zhang, Xiaofei He, Jianfeng Yan, Ligong Lu*, Jie Tian*. CT-based radiomics to predict development of macrovascular invasion in hepatocellular carcinoma: A multicenter study. Hepatobiliary & Pancreatic Diseases International, 2022, 21(4): 325-333.
(4) Jingwei Wei#, Hanyu Jiang#, Mengsu Zeng#, Meiyun Wang, Meng Niu, Dongsheng Gu, Huanhuan Chong, Yanyan Zhang, Fangfang Fu, Mu Zhou, Jie Chen, Fudong Lyv, Hong Wei, Mustafa R. Bahir, Bin Song, Hongjun Li*, Jie Tian*. Prediction of microvascular invasion in hepatocellular carcinoma via deep learning: a multi-center and prospective validation study. Cancers, 2021, 13(10), 2368.
(5) Jingwei Wei#, Lianwang Li#, Yuqi Han#, Dongsheng Gu, Qian Chen, Junmei Wang, Runting Li, Jiong Zhan, Jie Tian*, Dabiao Zhou*. Accurate preoperative distinction of intracranial hemangiopericytoma from meningioma using a multihabitat and multisequence-based radiomics diagnostic technique. Frontiers in Oncology, 2021, 10:534.
(6) Jingwei Wei#, Jin Cheng#, Dongsheng Gu#, Fan Chai, Nan Hong, Yi Wang*, Jie Tian*. Deep learning‐based radiomics predicts response to chemotherapy in colorectal liver metastases. Medical Physics, 2020, 48(1):531-522.
(7) Jingwei Wei#, Hanyu Jiang#, Dongsheng Gu#, Meng Niu, Fangfang Fu, Yuqi Han, Bin Song, Jie Tian*. Radiomics in liver diseases: Current progress and future opportunities. Liver International, 2020, 00:1-14.
(8) Jingwei Wei#, Guoqiang Yang#, Xiaohan hao, Dongsheng Gu, Yan Tan, Xiaochun Wang, Di Dong, Shuaitong Zhang, Le Wang, Hui Zhang*, Jie Tian*. A multi-sequence and habitat-based MRI radiomics signature for preoperative prediction of MGMT promoter methylation in astrocytomas with prognostic implication. European Radiology, 2019, 29(2):877-888.
(9) Hanyu Jiang#, Jingwei Wei#, Fangfang Fu#, Hong Wei, Yun Qin, Ting Duan, Weixia Chen, Kunlin Xie, Jeong Min Lee, Mustafa R. Bashir, Meiyun Wang, Bin Song*, Jie Tian*. Predicting microvascular invasion in hepatocellular carcinoma: a dual-institution study on gadoxetate disodium-enhanced MRI. Liver International, 2022, 42(5): 1158-1172.
(10) Qi Yang#, Jingwei Wei#, Xiaohan Hao#, Dexing Kong#, Xiaoling Yu, Tianan Jiang, Junqing Xi, Wenjia Cai, Yanchun Luo, Xiang Jing, Yilin Yang, Zhigang Cheng, Jinyu Wu, Huiping Zhang, Jintang Liao, Pei Zhou, Yu Song, Yao Zhang, Zhiyu Han, Wen Cheng, Lina Tang, Fangyi Liu, Jianping Dou, Rongqin Zheng, Jie Yu*, Jie Tian*, Ping Liang*. Improving B-mode ultrasound diagnostic performance for focal liver lesions using deep learning: A multicentre study. Ebiomedicine, 2020, 56:102777.
(11) Jin Cheng#, Jingwei Wei#, Tong Tong#, Weiqi Sheng#, Yinli Zhang, Yuqi Han, Dongsheng Gu, Nan Hong, Yingjiang Ye, Jie Tian*, Yi Wang*. Prediction of Histopathologic Growth Patterns of Colorectal Liver Metastases with a Noninvasive Imaging Method. Annals of Surgical Oncology, 2019, 26:4587-4598.
(12) Sirui Fu#, Jingwei Wei#, Jie Zhang#, Di Dong#, Jiangdian Song, Yong Li, Chongyang Duan, Shuaitong Zhang, Xiaoqun Li, Dongsheng Gu, Xudong Chen, Xiaohan Hao, Xiaofeng He, Jianfeng Yan, Zhenyu Liu, Jie Tian*, Ligong Lu*. Selection between Liver Resection versus Transarterial Chemoembolization in Hepatocellular Carcinoma: A Multicenter Study. Clinical and Translational Gastroenterology, 2019, 10:e-00070.
(13) Xiaohong Ma#, Jingwei Wei#, Dongsheng Gu, Yongjian Zhu, Bing Feng, Meng Liang, Shuang Wang, Xinming Zhao*, Jie Tian*. Preoperative Radiomics Nomogram for Microvascular Invasion Prediction in Hepatocellular Carcinoma using Contrast-enhanced CT. European Radiology, 2019, 29(7): 3595-3605.
(14) Yuqi Han#, Fan Chai#, Jingwei Wei#, Yali Yue#, Jin Cheng, Dongsheng Gu, Yinli Zhang, Tong Tong, Weiqi Sheng, Nan Hong, Yingjiang Ye, Yi Wang*, Jie Tian*. Identification of predominant histopathological growth patterns of colorectal liver metastasis by multihabitate and multisequence based radiomics analysis. Frontiers in Oncology, 2020, 10:1363.
(15) Dongshegn Gu#, Yongsheng Xie#, Jingwei Wei#, Wencui Li#, Zhaoxiang Ye, Zhongyuan Zhu, Jie Tian*, Xubin Li*. MRI-Based Radiomics Signature: A Potential Biomarker for Identifying Glypican 3-Positive Hepatocellular Carcinoma. Journal of Magnetic Resonance Imaging, 2020, 52(6):1679-1687.
(16) Gumuyang Zhang#, Yuqi Han#, Jingwei Wei#, Yafei Qi, Dongsheng Gu, Jing Lei, Weigang Yan, Yu Xiao, Huadan Xue, Feng Feng, Hao Sun*, Zhengyu Jin*, Jie Tian*. Radiomics Based on MRI as a Biomarker to Guide Therapy by Predicting Upgrading of Prostate Cancer from Biopsy to Radical Prostatectomy. Journal of Magnetic Resonance Imaging, 2020, 52(4):1239-1248.
(17) Li Yang#, Dongsheng Gu#, Jingwei Wei#, Chun Yang, Shengxiang Rao, Wentao Wang, Caizhong Chen, Ying Ding, Jie Tian*, Mengzu Zeng*. A Radiomics Nomogram for Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma. Liver Cancer, 2019, 8(5): 373-386.
(18) Shuaitong Zhang#, Shengyu Huang#, Wei He#, Jingwei Wei#, Lei Huo, Ningyang Jia, Jianbo Lin, Zhenchao Tang, Yunfei Yuan, Jie Tian*, Feng Shen*, Jun Li*. Radiomics-Based Preoperative Prediction of Lymph Node Metastasis in Intrahepatic Cholangiocarcinoma Using Contrast-Enhanced Computed Tomography. Annals of Surgical Oncology, 2022, 29(11): 6786-6799.
(19) Haifeng Zhou#, Yuqi Han#, Jian Lu#, Jingwei Wei#, Jinhe Guo#, Haidong Zhu#, Ming Huang, Jiansong Ji, Weifu Lv, Li Chen, Guangyu Zhu, Zhicheng Jin, Jie Tian*, Gaojun Teng*. Radiomics facilitates candidate selection for irradiation stents among patients with unresectable pancreatic cancer. Forntiers in Oncology, 2019, 9:973.
(20) 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.
(21) Haopeng Kuang, Dingkang Yang, Shunli Wang, Xue Yang, Hongjun Li, Jingwei Wei*, Lihua Zhang*. Adaptive Multi-Phase Liver Tumor Segmentation with Multi-Scale Supervision. IEEE Signal Processing Letters, 2024.
(22) Jie Tian, Di Dong, Zhenyu Liu, Jingwei Wei. Radiomics and Its Clinical Application: Artificial Intelligence and Medical Big Data, ISBN: 9780128181010, Imprint: Academic Press, Published Date: 3rd June 2021.
(23) Jie Tian, Di Dong, Zhenyu Liu, Yali Zang, Jingwei Wei, Jiangdian Song, Wei Mu, Shuo Wang, Mu Zhou. Radiomics in medical imaging—detection, extraction and segmentation[M]//Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging. Springer, Cham, 2018: 267-333.
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