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包立君

发布时间:2017-06-09 浏览次数:71

姓名: 包立君

职称、职位:助理教授

邮箱:baolijunATxmu.edu.cn

电话:13178350576

办公地点:物理大楼331


学历:

2007.1–2008.1 法国国立应用科学学院国家医学信号与图像应用技术研究中心(CREATIS)联合培养博士生

2005.9–2010.9 哈尔滨工业大学,电气工程及自动化学院,博士

2003.9–2005.7 哈尔滨工业大学,电气工程及自动化学院,硕士

1999.9–2003.7 燕山大学,电气工程及自动化学院,学士

研究方向

信号与图像处理算法,医学影像处理与分析,磁共振成像新方法及其应用

主讲课程:

MATLAB程序设计(本科生)

电子电路EDA(本科生)

现代传感器与检测技术(本科生)

矩阵论(研究生)

学术兼职:

ISMRM Annual Meeting Program Committee, 国际磁共振协会年会程序委员

国际磁共振学会ISMRM会员,国际电气电子工程师学会IEEE会员

国家自然科学基金通讯评审专家

成果奖励:

201704月厦门大学校庆厦航奖教金

201607月厦门大学物理科学与技术学院优秀党员

201403月国家留学基金委全额资助访问学者项目

201212月厦门大学第七届青年教师技能大赛二等奖

201011月第十六届全国波谱学学术会议优秀墙报银奖

课题项目:

主持

定量磁化率成像及其在脑白质纤维重建中的应用,国家自然科学基金81301277, 2014.01.01-2016.12.31

磁共振定量磁化率成像方法及其在脑部的应用研究,教育部博士点基金,20130121120010, 2014.01.01-2017.03.31

 磁共振定量磁化率成像方法及其纤维束示踪应用研究,福建省自然科学基金2014J05099, 2014.01.01-2016.12.31

参与在研

基于稀疏表示和深度学习方法实现新型时空编码MRI图像超分辨率重建,国家自然科学基金,616013892017/1-2019/12,排名2

实时三维时空编码磁共振成像的序列设计及重建算法研究,国家自然科学基金,816716742017/1-2020/12,排名4

基于低秩Hankel矩阵的快速高维磁共振波谱重建,国家自然科学基金,615713802016/1-2019/12,排名4

参与完成

超快速二维和多维高分辨核磁共振波谱新技术及其应用,国家自然科学基金111742392012.01-2015.12排名4

不均匀磁场下提高核磁共振波谱分辨率的新技术,国家自然科学基金11105114 2012.01-2014.12排名4

强磁场下大型哺乳动物新型磁共振成像技术与方法的开发与应用,国家自然科学基金U12322122013.01-2016.12排名10


代表作:

[1]Bao Lijun*, Li Xu*, Cai Congbo, Chen Zhong, van Zijl C.M. Peter, 2016. Quantitative susceptibility mapping using structural feature based collaborative reconstruction (SFCR) in the human brain. IEEE Transactions on Medical Imaging 35(9):2040-2050.(IEEE: SCIJCR2IF3.84)

[2]Fang Jinsheng, Bao Lijun*, Li Xu, van Zijl C. M. Peter, Chen Zhong*, 2017. Background field removal using a region adaptive kernel for quantitative susceptibility mapping of human brain. Journal of Magnetic Resonance, May 10, doi.org/10.1016/j.jmr.2017.05.004(SCI JCR2)

[3]Cai Congbo*, Zeng Yiqing, Zhuang Yuchuan, Cai Shuhui, Chen Lin, Ding Xinghao, Bao Lijun, Zhong Jianhui, Chen Zhong, 2017. Single-shot T2 mapping through Overlapping-echo detachment (OLED) planar imaging. IEEE Transactions on Biomedical Engineering. Jan 31, doi: 10.1109/TBME. 2017.2661840 (IEEE: SCIJCR2 )

[4]Chen Lin, Zheng Zhiwei, Bao Lijun, Cai Shuhui*, Cai Congbo*, Chen Zhong,2017. Weighted total variation using split Bregman: a fast quantitative susceptibility mapping reconstruction method. May 10, submitted to Physics in Medicine and Biology.(SCI JCR3)

[5]Zhu Liuhong, Cheng Qihua, Luo Wenbin, Bao Lijun, Guo Gang*,2015. A comparative study of apparent diffusion coefficient and intravoxel incoherent motion derived parameters for the characterization of common solid hepatic tumors, Acta Radiologica. 56(12): 1411-1418.(SCI)

[6]Bao Lijun*, Robini Marc, Liu Wanyu, Zhu Yuemin, 2013. Structure-adaptive sparse denoising for diffusion-tensor MRI. Medical Image Analysis.17: 442-457.(SCI JCR1,IF4.2)

[7]Cai Congbo, Dong Jiyang, Cai Shuhui, Li Jing, Chen Ying, Bao Lijun, Chen Zhong*, 2013. An efficient de-convolution reconstruction method for spatiotemporal-encoding single-scan 2D MRI. Journal of Magnetic Resonance, 228:136-147.(SCI JCR2)

[8]Chen Lin, Bao Lijun, Li Jing, Cai Shuhui*, Cai Congbo*, Chen Zhong,2013. A novel hybrid reconstruction method for random undersampling spatiotemporally encoded single-shot MRI. Journal of Magnetic Resonance, 237:115-124.(SCI JCR2)

[9]Liu Hongfei, Bao Lijun, Chen Qiuxia, Chen Zhong*, 2011. A high-precision 1D dynamic angular measuring system based on linear CCD for Fengyun-2 meteorological satellite. Journal of optic and laser technology. 43:1306-1313.(SCI)

[10]Hu Changwei, Qu Xiaobo, Guo Di, Bao Lijun, Chen Zhong*,2011. Wavelet-based edge correlation incorporated iterative reconstruction for undersampled MRI. Magnetic Resonance Imaging, 29: 907-915.(SCI)

[11]包立君*, 刘宛予, 浦昭邦, 2011. 融合图像局部能量和梯度的水平集分割方法.哈尔滨工业大学学报, 43:44-48.(EI)

[12]Bao Lijun*, Zhu Yuemin, Liu Wanyu, P Croisille, Pu Zhaobang, Robini Marc, Isabelle E Magnin, 2009. Denoising of human cardiac diffusion tensor magnetic resonance images using sparse representation combined with segmentation. Physics in Medicine and Biology. 54: 1435-1456.(SCI JCR3)

[13]Bao Lijun*, Pu Zhaobang, Tang Wenyan, 2006. Aviation springwire socket measurement system based on computer vision. Semiconductor Optoelectronics. 27(3):333-336(In Chinese, EI)

Conference

[1]Jinsheng Fang, BaoLijun*, Zhong Chen. A New Background Field Removal Method Using Region Adaptive Kernel for Human Brain MRI, 2017 ISMRM Annual Meeting, Hawaii USA.2017.04. (oral presentation)

[2]Bao Lijun. Image Super-resolution Restoration based on Structure Feature in Fourier Domain for MR Images. 2016 ISMRM Annual Meeting, Singapore.2016.05.

[3]BaoLijun*, Zhong Chen, Peter C.M. van Zijl, and Xu Li. Structural feature based collaborative reconstruction for quantitative susceptibility mapping. 2015 ISMRM Annual Meeting, Montreal Canada.2015.05.

[4]Bao Lijun*, Liu Wanyu, Qu Xiaobo, Cai Shuhui, Chen Zhong. Three dimensional restoration of cardiac magnetic resonance diffusion weighted images based on sparse denoising. 2011 ISMRM Annual Meeting, Montreal Canada.2011.05.

[5]Bao Lijun*, Zhu Yuemin, Liu Wanyu, Pu Zhaobang, Robini Marc, Isabelle E Magnin, 2007. Analysis of cardiac diffusion tensor magnetic resonance images using sparse representation. Annual International Conference of the IEEE Engineering in Medicine and Biology, Lyon, France. 4516-4519.

[6]Bao Lijun*, Zhang Zhuo, Liu Guodong, Pu Zhaobang. ICF Laser target alignment sensor calibration system. Proceedings of SPIE, Harbin China. 2007, v 6595 I:659505, 1-5.

国家发明专利:

[1]包立君,李明汉,熊丛丛,蔡聪波,陈忠. 基于结构特征的自适应定量磁化率分布图复合重建的方法.公开号:CN104267361A.

[2]包立君,叶富泽. 一种基于傅里叶频谱特征的图像块聚类方法. 申请号:201710080210.X.

[3]包立君,方金生,陈忠. 一种基于自适应卷积核的磁共振相位图的背景场去除方法. 申请号:201710300868.7.