学历与工作
2010年毕业于哈尔滨工业大学仪器科学与技术专业，工学博士
2007–2008年法国里昂国立应用科学学院(INSA Lyon)，博士联培
2014–2015年美国约翰霍普金斯大学医学院，访问学者
2010.09至今厦门大学电子科学系助理教授、副教授
研究方向
智能影像、计算成像、电子技术
主讲课程
MATLAB程序设计，现代传感器与检测技术，矩阵论
学术兼职
曾任国际医学磁共振学会年会程序委员ISMRM AMPC
现任中国图象图形学学会视觉检测专委会、中国生物医学工程学会医学影像分会委员
国家自然科学基金评审，福建省科学基金项目评审，国际主流期刊审稿
成果奖励
中国研究生电子设计竞赛全国总决赛团队一等/优秀指导教师
ISMRM国际医学磁共振协会E.K.Zavoisky奖金
国际定量磁化率成像重建QSM Challenge算法竞赛冠军
厦门大学厦航奖教金、闽都国际银行奖教金
厦门大学第六届英语教学比赛、第七届青年教师技能大赛二等奖
课题项目
国家自然科学基金面上项目，基于机器学习的多参数脑部定量磁化率成像研究，2021-2024，主持
中国工程物理研究院横向项目，数字全息粒子场在焦状态智能判断程序，2022-2024，主持
福建省自然科学基金面上项目，精准定量磁化率成像技术及其应用的关键问题研究，2019-2022，主持
中国工程物理研究院横向项目，粒子场判读神经网络研制，2019-2021，主持
国家自然科学基金青年项目，定量磁化率成像及其在脑白质纤维重建中的应用，2014-2016，主持
教育部博士点基金，磁共振定量磁化率成像方法及其在脑部的应用研究，2014-2016，主持
福建省自然科学基金青年项目，磁共振定量磁化率成像方法及其纤维束示踪应用研究，2014-2017，主持
代表性成果
l Zewen Wang, Hsinyu Liu, Dongkai Yang, Lijun Bao*, The luminous efficiency of InGaN/GaN based green microLED improved by n-side graded quantum wells, Optics Letters, 2025, 50(9), DOI 10.1364/OL.558409.
l Lijun Bao#, Bingsen Chen#, Li Chen, Jintao Chen, Peng Zhuang, Guolong Chen, Zhong Chen, Lihong Zhu*, Yijun Lu*, Multichannel goniospectrometer system for near-field and far-field light spatial distribution, IEEE Transactions on Instrumentation and Measurement, 2025, 74, 7002807.
l Lichu Qiu, Zijun Zhao, Lijun Bao*, SIPAS: A comprehensive susceptibility imaging process and analysis studio, NeuroImage, 2024, 297, 120697.
l Lijun Bao*, Hongyuan Zhang, Zeyu Liao, A spatially adaptive regularization based three-dimensional reconstruction network for quantitative susceptibility mapping, Physics in Medicine and Biology, 2024, 69, 045030.
l Jiaxiu Xi, Yuqing Huang, Lijun Bao*, Quantitative susceptibility mapping based basal ganglia segmentation via AGSeg: leveraging active gradient guiding mechanism in deep learning, Quantitative Imaging in Medicine and Surgery, 2024, 14(7): 4417-4435.
l Hsin-Yu Liu, Donghao Zhang, Zhongying Zhang, Chaohsu Lai, Zongmin Lin, Chia-En Lee, Lijun Bao*, Sheng-PoChang, Shoou-Jinn Chang*, Fabrication of high efficiency green InGaN/GaN MicroLEDs by modulating potential barrier height of the sidewall MQWs in V-pits, IEEE Photonics Journal, 2024, 16(3): 1-9.
l Lijun Bao#*, Qiuyang Zhao#, Yu Zhao, A primary-auxiliary coupled neural network for 3D holographic particle field characterization, IEEE Transactions on Industrial Informatics, Volume 18, 2022, 18: 6671-6679.
l Lijun Bao*, Congcong Xiong, Wenping Wei, Zhong Chen, Peter C.M.van Zijl, Xu Li, Diffusion-regularized susceptibility tensor imaging (DRSTI) of tissue microstructures in the human brain. Medical Image Analysis, Volume 67, 101827, 2021.
l Lijun Bao*, Fuze Ye, Congbo Cai, Jian Wu, Kun Zeng, Peter C.M. van Zijl, Zhong Chen, Undersampled MR image reconstruction using an enhanced recursive residual network, Journal of Magnetic Resonance, 2019, 305: 232-246.
l Jinsheng Fang, Lijun Bao*, Xu Li, Peter C.M. van Zijl, Zhong Chen, Background field removal for susceptibility mapping of human brain with large susceptibility variations, Magnetic Resonance in Medicine, 2019, 81: 2025-2037.
l Lijun Bao*, Xu Li*, Congbo Cai, Zhong Chen, Peter C.M. van Zijl, Quantitative susceptibility mapping using structural feature based collaborative reconstruction (SFCR) in the human brain. IEEE Transactions on Medical Imaging, 2016, 35(9):2040-2050.
l Lijun Bao*, Marc Robini, Wanyu Liu*, Yuemin Zhu, Structure-adaptive sparse denoising for diffusion-tensor MRI. Medical Image Analysis, 2013, 17:442-457.
l Lijun Bao*, Yuemin Zhu, Wanyu Liu, Croisille Pierre, Zhaobang Pu, Marc Robini, Isabelle E Magnin, Denoising human cardiac diffusion tensor magnetic resonance images using sparse representation combined with segmentation, Physics in Medicine and Biology, 2009, 54:1435-1456.
