三、主要科研工作与成绩 【科研项目】 负责国家自然科学基金面上项目《基于Wasserstein生成式对抗网络的冠状动脉CT血管成像运动伪影去除研究》，项目编号：81971612；起止时间：2020.1-2023.12；在研。 负责上海市第一人民医院临床研究创新团队(D类)《深度卷积神经网络对肺腺癌病理学分型和术后预后评估的内部运行机理可视化研究》项目编号：CTCCR-2019D05，起止时间：2019.12-2022.12；在研。 负责上海交通大学转化医学交叉研究重点项目，《基于生成式对抗网络(GAN)的冠状动脉CT血管成像伪影补偿研究》项目编号ZH2018ZDB10，起止时间：2019.1-2021.12；在研。 负责浦东新区科技发展基金产学研专项资金《5G传输技术支撑的基于计算机视觉和自然语言处理的胸部疾病筛查智能辅助诊断系统的研究和应用》；PKX2019-R02，起止时间2020.1-2021.12；结题。 负责上海交通大学医学院高峰学科—临床医学“研究型医师”人才项目，《肺腺癌影像学深度学习临床研究》项目编号20181814，起止时间：2019.1-2021.12；结题。 负责上海市第一人民医院临床研究创新团队(B类)《深度学习影像分析对肺结节病理和肺腺癌基因学预测和诊断模型建立》项目编号CTCCR-2018B04，起止时间：2018.1-2021.12；结题。 负责国家科技部国际合作重点专项(中国科技部-荷兰卫生部中荷战略科学联盟计划)《超低剂量胸部CT对肺癌、心血管疾病和COPD的筛查》项目编号：2016YFE0103000；起止时间：2017.1-2021.12，在研。 负责上海市科委医学引导类（中、西医）科技支撑项目《基于肺磨玻璃结节(GGN)生长特性的肺腺癌早期诊断研究》项目编号：16411968500;起止时间：2016.7.1-2019.6.30；结题。 负责上海市科委国际合作项目《基于肺磨玻璃结节(GGN)生长特性数据库的早期肺腺癌影像学诊断研究》项目编号：16410722300；起止时间：2016.07.01-2019.06.30；结题。 负责国家自然科学基金面上项目《基于冠状动脉钙化斑块伪影特征识别的非门控CT钙化积分定量研究》项目编号：81471662；起止时间：2015.1-2018.12；结题。
【论文】 Lu Zhang, Zhihan Xu, BeibeiJiang, Yaping Zhang, Lingyun Wang, Geertruida H deBock，RozemarijnVliegenthart, Xueqian Xie*. Machine-learning-based radiomicsidentifies atrial fibrillation on the epicardial fat incontrast-enhanced and non-enhanced chest CT. British Journal ofRadiology.2022;95:20211274 Beibei Jiang, Nianyun Li,Xiaomeng Shi, Shuai Zhang, Jianying Li, Geertruida H. de Bock,Rozemarijn Vliegenthart, Xueqian Xie*. Deep learningreconstruction shows better lung nodule detection forultra-low-dose chest CT. Radiology.2022;303(1):202-12 Lin Zhang, Beibei Jiang,Hendrik Joost Wisselink, Rozemarijn Vliegenthart, Xueqian Xie*.COPD identification and grading based on deep learning of lungparenchyma and bronchial wall in chest CT images. British Journalof Radiology.2022;95:20210637 Yaping Zhang, Beibei Jiang,Lu Zhang, Marcel Greuter, Geertruida H. de Bock, Hao Zhang,Xueqian Xie*. Lung Nodule Detectability of ArtificialIntelligence-assisted CT Image Reading in Lung Cancer Screening.Current Medical Imaging.2022;18(3):327-34 Magdalena Dobrolińska, Nielsvan der Werf, Marcel Greuter, Beibei Jiang, Riemer Slart, XueqianXie*. Classification of moving coronary calcified plaques basedon motion artifacts using convolutional neural networks: arobotic simulating study on influential factors. BMC MedicalImaging.2021;21(1):151 Yaping Zhang, Mingqian Liu,Shundong Hu, Jun Lan, Beibei Jiang, Geertruida H. de Bock, XuChen, Rozemarijn Vliegenthart, Xueqian Xie*. Development andmulticenter validation of chest X-ray radiography interpretationsbased on natural language processing. CommunicationsMedicine.2021;1:43 Guixue Liu, Zhihan Xu, YapingZhang, Beibei Jiang, Lu Zhang, Lingyun Wang, Geertruida H. deBock, Rozemarijn Vliegenthart, Xueqian Xie*.Machine-learning-derived nomogram based on 3D radiomic featuresand clinical factors predicts progression-free survival in lungadenocarcinoma. Frontiers in Oncology.2021;11:692329 Lu Zhang, Jianqing Sun,Beibei Jiang, Lingyun Wang, Yaping Zhang, Xueqian Xie*.Development of artificial intelligence in epicardial andpericoronary adipose tissue imaging. European Journal of HybridImaging.2021;5(1):14 Tiening Zhang, Zhihan Xu,Guixue Liu, Geertruida H. de Bock, Harry JM Groen, RozemarijnVliegenthart, Xueqian Xie*. Simultaneous identification of EGFR,KRAS, ERBB2, and TP53 mutations in patients with non-small celllung cancer by machine learning-derived three-dimensionalradiomics. Cancers.2021;13(8):1814 Beibei Jiang, Yaping Zhang,Lu Zhang, Geertruida H. de Bock, Rozemarijn Vliegenthart, XueqianXie*. Human-recognizable CT image features of subsolid lungnodules associated with diagnosis and classification byconvolutional neural networks. EuropeanRadiology.2021;31(10):7303-15 Guixue Liu, Zhihan Xu,Yingqian Ge, Harry Groen, Rozemarijn Vliegenthart, Xueqian Xie*.3D radiomics predicts EGFR mutation, exon-19 deletion and exon-21L858R mutation in lung adenocarcinoma. Translational Lung CancerResearch.2020;9(4):1212-24 Lin Zhang, Gert Jan Pelgrim,Jing Yan, Hao Zhang, Rozemarijn Vliegenthart, Xueqian Xie*.Feasibility of bronchial wall quantification in low- andultralow-dose third-generation dual-source CT: an ex vivo lungstudy. Journal of Applied Clinical MedicalPhysics.2020;21(10):218-26 Beibei Jiang, Ning Guo,Yinghui Ge, Lu Zhang, Matthijs Oudkerk, Xueqian Xie*. Developmentand application of artificial intelligence in cardiac imaging.British Journal of Radiology.2020;93(1113):20190812 Yaping Zhang, Niels R. vander Werf, Beibei Jiang, Robbert van Hamersvelt, Marcel J.W.Greuter, Xueqian Xie*. Motion corrected coronary calcium scoresby a convolutional neural network: a robotic simulatingstudy.European Radiology.2020;30(2):1285-94 Yifeng He, Jiapan Guo, XiaoyiDing, Peter M.A. van Ooijen, Yaping Zhang, An Chen, MatthijsOudkerk, Xueqian Xie*. Convolutional neural network to predictthe local recurrence of giant cell tumor of bone after curettagebased on pre-surgery magnetic resonance images. EuropeanRadiology.2019;29(10):5441-51 Lin Zhang, Zhengyu Li, JieMeng, Xueqian Xie*, Hao Zhang*. Airway quantification usingadaptive statistical iterative reconstruction-V on wide-detectorlow-dose CT: a validation study on lung specimen. JapaneseJournal of Radiology. 2019;37(5):390-8 YapingZhang, Marjolein A Heuvelmans, Hao Zhang, Matthijs Oudkerk,Guixiang Zhang, Xueqian Xie*. Changes of quantified CT imagefeatures of ground-glass nodules in differentiating invasivepulmonary adenocarcinoma: histopathologic comparisons. ClinicalRadiology. 2018;73(5):504.e9-e16
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