计算机与信息工程学院

郭迪


女,1982年出生,博士,教授,硕士生导师,计算感知实验室(厦门理工学院)负责人。入选厦门市高层次人才、鹭江学者、福建省女科技工作者协会厦门理工学院分会理事会委员等。2012年在厦门大学获得通信与信息系统专业博士学位,2009-2011年、2018-2019年获得国家留学基金委资助到美国华盛顿大学电子工程系访学。

长期从事医学成像、人工智能、机器学习、云计算、磁共振的研究和产业化,获得福建省自然科学一等奖(排名第三)。主持国家自然科学基金面上项目、青年项目各1项,福建省自然科学基金2项,厦门市产学研项目1项,以第一合作人承担国家自然科学基金2项。授权发明专利4项,发表被SCI/EI检索的学术论文50余篇,论文被引超2200多次(Google Scholar)。多次指导学生获得研究生国家奖学金、人工智能创新创业竞赛奖等。

Email: guodi AT xmut.edu.cn


  教育背景:

  ·2018/10- 2019/09 美国 华盛顿大学,电子工程系,访问学者

  ·2006/09 - 2012/06,厦门大学,通信与信息系统, 工学博士(提前攻博)

  ·2009/10- 2011/10 美国 华盛顿大学,电子工程系,博士研究生(联合培养)

  ·2006/09 - 2008/07厦门大学,通信与信息系统, 工学硕士研究生

  ·2001/09 - 2005/07厦门大学,通信工程,工学学士

  

工作经历:

  ·2021/12 - 至今,厦门理工学院,计算机与信息工程学院,教授

  ·2019/08 - 2021/12厦门理工学院,计算机与信息工程学院,预聘教授

  ·2015/07 - 2019/07厦门理工学院,计算机与信息工程学院,副教授

  ·2012/05 - 2015/06厦门理工学院,计算机与信息工程学院,讲师

    

科研项目:

[1] 国家自然科学基金面上项目基于超复数的高保真磁共振波谱重建6187134158万),2019.01-2022.12,主持。

[2] 国家自然科学基金青年项目基于拓扑结构的无线传感网多模数据稀疏修复6130217424万),2014.01-2016.12,主持。

[3] 国家自然科学基金面上项目基于空间-谱间自适应自稀疏表示的高光谱压缩成像方法研究61672335,分30%18.9万),2017.01-2020.12,第2位。

[4] 国家自然科学基金青年项目低成本高光谱压缩采样与结构化稀疏重建61601276,分35%8.5万),2017.01-2019.12,第2位。

[5] 国家自然科学基金青年项目空间编码可控的快速 MRI 高分辨率图像稀疏重建61201045),2013.01-2015.12,第4位。

[6] 福建省自然科学基金面上项目“磁共振波谱超复数神经网络与超快速重建”(2021J0111847万),2021.08-2024.08,主持。

[7] 福建省自然科学基金项目基于低秩张量表示的快速磁共振成像2016J052053万),2016.04-2019.04,主持。

[8] 福建省自然科学基金项目印刷体QR二维条码防伪数字水印技术研究2016J01327),2016.04-2019.04,第3位。

[9] 福建省自然科学基金项目基于X线光谱图像的食源性有害物质的快速检测算法研究2014J01256),2014.01-2016.12,第3位。

[10] 厦门市产学研协同创新及科技合作项目“快速磁共振波谱的高质量重建方法研究”(3502Z2018305310) 2018.03-2020.03,主持。

[11] 广东省数字信号与图像处理技术重点实验室开放基金传感网多模数据的稀疏修复2013GDDSIPL-072万)2013.08-2015.07,主持。

[12] 厦门理工学院人才引进项目位置透明的传感网多模数据稀疏修复YKJ12021R6万),2012.11-2014.12,主持。


发表论文:*表示通信作者,#表示共同一作

[1] Zi Wang, Di Guo, Zhangren Tu, Yihui Huang, Yirong Zhou, Jian Wang, Liubin Feng, Donghai Lin, Yongfu You, Tatiana Agback, Vladislav Orekhov, Xiaobo Qu*, A sparse model-inspired deep thresholding network for exponential signal reconstruction—application in fast biological spectroscopy, IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2022.3144580, 2022. (SCI, JCR 1, IF 10.45)

[2] Gushan Zeng (研究生), Yi Guo, Jiaying Zhan, Zi Wang, Zongying Lai, Xiaofeng Du, Xiaobo Qu, Di Guo*, A review on deep learning MRI reconstruction without fully sampled k-space, BMC Medical Imaging, 21(195) DOI: 10.1186/s12880-021-00727-9, 2021. (SCI, JCR 4, IF 1.93)

[3] Di Guo, Jiaying Zhan, Yirong Zhou, Zhangren Tu, Zifei Zhang, Zhong Chen, Xiaobo Qu*, Low-rank and sparse reconstruction for fast diffusion nuclear magnetic resonance spectroscopy, IET Signal Processing, 15: 88-97, 2021. (SCI, JCR 4, IF 1.43)

[4] Zhangren Tu (研究生), Zi Wang, Jiaying Zhan, Yihui Huang, Xiaofeng Du, Min Xiao, Xiaobo Qu, Di Guo*A partial sum of singular-value-based reconstruction method for non-uniformly sampled NMR spectroscopyIET Signal Processing, 15: 14-27, 2021. (SCI, JCR 4, IF 1.43)

[5] Xinlin Zhang, Hengfa Lu, Di Guo, Lijun Bao, Feng Huang, Qin Xu, Xiaobo Qu*, A guaranteed convergence analysis for the projected fast iterative soft-thresholding algorithm in parallel MRI, Medical Image Analysis, 69101987, 2021. (SCI, JCR 1, IF 11.15)

[6] Tianyu Qiu, Wenjing Liao, Yihui Huang, Jinyu Wu, Di Guo, Dongbao Liu, Xin Wang, Jian-Feng Cai, Bingwen Hu, Xiaobo Qu*, An automatic denoising method for NMR spectroscopy based on low-rank Hankel model, IEEE Transactions on Instrumentation & Measurement, vol. 70, pp. 1-12, 2021. (SCI, JCR 2, IF 4.02)

[7] Yihui Huang#, Jinkui Zhao#, Zi Wang, Vladislav Orekhov, Di Guo, Xiaobo Qu*, Exponential signal reconstruction with deep Hankel matrix factorization, IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2021.3134717, 2021. (SCI, JCR 1, IF 10.45)

[8] Yirong Zhou, Chen Qian, Yi Guo, Zi Wang, Jian Wang, Biao Qu, Di Guo, Yongfu You, Xiaobo Qu*, XCloud-pFISTA: A medical intelligence cloud for accelerated MRI, The 43th Annual International Conference of the IEEE Engineering in Medicine and Biology Society-EMBC’21, pp. 3289-3292, Oct 31 - Nov 4, 2021, Virtual Conference, 2021. (EI)

[9] Xinlin Zhang, Zi Wang, Xi Peng, Qin Xu, Di Guo, Xiaobo Qu*, Accelerated image reconstruction with separable Hankel regularization in parallel MRI, The 43th Annual International Conference of the IEEE Engineering in Medicine and Biology Society-EMBC’21, pp. 3403-3406, Oct 31 - Nov 4, 2021, Virtual Conference, 2021. (EI)

[10] 詹嘉莹(研究生), 涂章仁, 杜晓凤, 袁斌, 郭迪*, 屈小波, 基于低秩矩阵的非均匀采样NMR波谱重建进展, 波谱学杂志, 37卷,第3期,第255-272, 20209.[特邀综述, 封面文章,核心期刊]

[11] Zhangren Tu (研究生), Huiting Liu, Jiaying Zhan, Di Guo*, A fast self-learning subspace reconstruction method for non-uniformly sampled nuclear magnetic resonance spectroscopy, Applied Sciences, 10(11): 3939, 2020. (SCI, JCR 3, IF 1.86)

[12] Xinlin Zhang, Di Guo, Yiman Huang, Ying Chen, Liansheng Wang, Feng Huang, Qin Xu, Xiaobo Qu*, Image reconstruction with low-rankness and self-consistency of k-space data in parallel MRI, Medical Image Analysis, 63:101687, 2020. (SCI, JCR 1, IF 11.15)

[13] Dicheng Chen#, Zi Wang#, Di Guo, Vladislav Orekhov, Xiaobo Qu*, Review and Prospect: Deep learning in nuclear magnetic resonance spectroscopy, Chemistry - A European Journal, 26(46): 10391-10401, 2020. (# denotes co-first authorship) (SCI, JCR 2, TOP Journal, IF 5.16) [Invited Review, Frontispiece]

[14] Tianyu Qiu, Zi Wang, Huiting Liu, Di Guo, Xiaobo Qu*, Review and prospect: NMR spectroscopy denoising & reconstruction with low rank Hankel matrices and tensors, Magnetic Resonance in Chemistry, 59(3): 324-345, 2021. (SCI, JCR 3, IF 2.03) [Invited Review]

[15] Di Guo*, Zhangren Tu, Jiechao Wang, Min Xiao, Xiaofeng Du, Xiaobo Qu. Salt and pepper noise removal with multi-Class dictionary learning and L0 norm regularizations, Algorithms, 12(1): 7, 10.3390/a12010007, 2019. (EI)

[16] Xiaobo Qu*, Yihui Huang, Hengfa Lu, Tianyu Qiu, Di Guo, Tatiana Agback, Vladislav Orekhov, Zhong Chen*, Accelerated nuclear magnetic resonance spectroscopy with deep learning, Angewandte Chemie-International Edition, 59(26):10297-10300, 2020. (SCI, JCR 1, IF 15.34)

[17] Di Guo, Xiaobo Qu*. Improved reconstruction of low intensity magnetic resonance spectroscopy with weighted low rank Hankel matrix completion, IEEE Access, 6: 4933-4940, 2018. (SCI, JCR 2, IF 3.56)

[18] Xiaobo Qu*, Tianyu Qiu, Di Guo, Hengfa Lu, Jiaxi Ying, Ming Shen, Bingwen Hu, Vladislav Orekhov, Zhong Chen, High-fidelity spectroscopy reconstruction in accelerated NMR, Chemical Communications, 54(78): 10958-10961, 2018. (SCI, JCR 1, IF 6.29)

[19] Jiaxi Ying, Jian-Feng Cai, Di Guo, Gongguo Tang, Zhong Chen, Xiaobo Qu*, Vandermonde factorization of Hankel matrix for complex exponential signal recovery-application in fast NMR spectroscopy, IEEE Transactions on Signal Processing, 66(21):5520-5533, 2018. (SCI, JCR 2, TOP Journal, IF 4.30)

[20] Xiaofeng Du, Xiaobo Qu, Yifan He, Di Guo*.Single image super-resolution based on multi-scale competitive convolutional neural network, Sensors, 18(3): 789, 2018. (SCI, JCR 3, IF 2.68)

[21] Hengfa Lu, Xinlin Zhang, Tianyu Qiu, Jian Yang, Jiaxi Ying, Di Guo, Zhong Chen, Xiaobo Qu*, Low rank enhanced matrix recovery of hybrid time and frequency data in fast magnetic resonance spectroscopy, IEEE Transactions on Biomedical Engineering, 65(4): 809-820, 2018. (SCI, JCR 2, IF 3.58)

[22] Weiming Lin, Tong Tong, Qinquan Gao, Di Guo, Xiaofeng Du, Yonggui Yang, Gang Guo, Min Xiao, Min Du*, Xiaobo Qu*, and the Alzheimer’s Disease Neuroimaging Initiative, Convolutional neural networks-based MRI image analysis for the Alzheimer’s disease prediction from Mild cognitive impairment, Frontiers in Neuroscience, 12:777, 2018. (SCI, JCR 2, IF 3.88) [ESI高被引论文, 3%]

[23] Zongying Lai, Xinlin Zhang, Di Guo, Xiaofeng Du, Yonggui Yang, Gang Guo, Zhong Chen, Xiaobo Qu*, Joint sparse reconstruction of multi-contrast MRI images with graph based redundant wavelet transform, BMC Medical Imaging, 18(1):7, 2018. (SCI, JCR 4, IF 1.66)

[24] Di Guo, Hengfa Lu, Xiaobo Qu*, A fast low rank Hankel matrix factorization reconstruction method for non-uniformly sampled magnetic resonance spectroscopy, IEEE Access, 5: 16033-16039, 2017. (SCI, JCR 2, IF 3.56)

[25] Jiaxi Ying, Hengfa Lu, Qingtao Wei, Jian-Feng Cai, Di Guo, Jihui Wu, Zhong Chen, Xiaobo Qu*. Hankel matrix nuclear norm regularized tensor completion for N-dimensional exponential signals, IEEE Transactions on Signal Processing, 65(14): 3702-3717, 2017. (SCI, JCR 2, TOP Journal, IF 4.30)

[26] Zongying Lai, Xiaobo Qu*, Yunsong Liu, Di Guo, Jing Ye, Zhifang Zhan, Zhong Chen*. Image reconstruction of compressed sensing MRI using graph-based redundant wavelet transform, Medical Image Analysis, 27: 93-104, 2016. (SCI&EI, JCR 1, 3-Year IF 4.09) [ESI高被引论文, 3%]

[27] Yunsong Liu, Zhifang Zhan, Jian-Feng Cai, Di Guo, Zhong Chen, Xiaobo Qu*. Projected iterative soft-thresholding algorithm for tight frames in compressed sensing magnetic resonance imaging, IEEE Transactions on Medical Imaging, 35(9): 2130-2140, 2016. (SCI, JCR 2, IF 3.85) [ESI高被引论文, 3%]

[28] Zhifang Zhan, Jian-Feng Cai, Di Guo, Yunsong Liu, Zhong Chen, Xiaobo Qu*. Fast multi-class dictionaries learning with geometrical directions in MRI reconstruction, IEEE Transactions on Biomedical Engineering, 63(9):1850-1861, 2016. (SCI, JCR 2, IF 2.35) [ESI高被引论文, 3%]

[29] Di Guo, Jingwen Yan, Xiaobo Qu*. High quality multi-focus image fusion using self-similarity and depth information, Optics Communications, 338: 138-144, 2015. (SCI, JCR 3, IF 1.54)

[30] Yunsong Liu, Jian-feng Cai, Zhifang Zhan, Di Guo, Jing Ye, Zhong Chen, Xiaobo Qu*. Balanced sparse model for tight frames in compressed sensing magnetic resonance imaging, PLoS ONE, 10(4): e0119584, 2015. (SCI, JCR 2, IF 3.53) [ESI高被引论文, 1%]

[31] Di Guo, Xiaobo Qu, Meng Wu, Keshou Wu. A modified iterative alternating direction minimization algorithm for impulse noise removal in images, Journal of Applied Mathematics, Vol. 2014, Article ID 595782, 2014. (SCI, JCR 3, IF 0.83)

[32] Di Guo, Xiaobo Qu, Xiaofeng Du, Keshou Wu, and Xuhui Chen. Salt and Pepper noise removal with noise detection and a patch-based sparse representation, Advances in Multimedia, vol. 2014, Article ID 682747, 2014. (EI)

[33] Di Guo, Zicheng Liu, Xiaobo Qu, Lianfen Huang*, Yan Yao, Ming-Ting Sun. Sparsity-based online missing data recovery using overcomplete dictionary, IEEE Sensors Journal, 12(7): 2485-2495, 2012. (SCI, JCR 3, IF 1.47)

[34] Di Guo, Xiaobo Qu, Lianfen Huang*, Yan Yao. “Optimized local superposition in wireless sensor networks with t-average-mutual-coherence,” Progress in Electromagnetics Research, 122: 389-411, 2012. (SCI, JCR 2, IF 3.76)

[35] Di Guo, Xiaobo Qu, Lianfen Huang, Yan Yao, Zicheng Liu, Ming-Ting Sun. “Sparsity-based online missing sensor data recovery,” 2012 IEEE Int. Symp. Circuits and Systems-ISCAS 2012, May 20-23, Seoul, Korea, pp. 918-921. (EI) [Oral presentation, win student grant KRW550,000]

[36] Di Guo, Xiaobo Qu, Lianfen Huang, Yan Yao. “Sparsity-based spatial interpolation in wireless sensor networks, Sensors,” 11(3): 2385-2407, 2011. (SCI, JCR 2, IF 1.77)

  

发明专利:

 [1] 一种欠采样磁共振波谱的快速重建方法. 专利号:ZL201611011513.8, 1.

 [2] 一种联合小波变换域和空间域的医学图像融合方法. 专利号:ZL201510703487.4, 1.

 [3] 一种联合空间-时间稀疏性的传感网数据恢复方法. 专利号:ZL201611011663.9, 1.

 [4] 一种高保真谱重建方法. 专利号:ZL2018105104594, 1.

 [5] 一种基于截断核范数的磁共振波谱重建方法. 中国, 申请号:201810817979.X,第1.

 [6] 一种基于部分奇异值和的磁共振波谱重建方法. 中国, 申请号:201810903898.1, 1.

 [7] 一种基于子空间的磁共振波谱快速重建方法. 中国, 申请号:2020102862747, 1.

 [8] 一种人工智能多对比度磁共振快速成像方法. 中国, 申请号:2021115219596, 1.


获奖:

[1] 《快速磁共振波谱成像方法及应用》,2020年度福建省自然科学奖一等奖,排名第三(第二完成单位),福建省人民政府,2021.12

[2] 厦门市高层次人才(C类), 2019

[3] 厦门理工学院 鹭江青年学者,2018.10-至今;

[4] 厦门理工学院庆祝三八妇女节诗歌朗诵比赛二等奖,2021.03

[5] 25IEEE电路与系统年会(ISCAS 2012)学生资助奖,2012.05

[6] IBM中国优秀学生奖学金,2012.12


指导学生获奖:

[1] 2019.12作为指导教师在福建省研究生人工智能学科竞赛获声纹识别组团队二等奖;

[2] 2019.12作为指导教师在福建省研究生人工智能学科竞赛获车牌识别组团队二等奖;

[3] 2020.12作为指导教师的作品《快速自学习子空间重建方法》获厦门理工学院第五届研究生学术活动月创新成果展二等奖;

[4] 2020.12作为指导教师的作品《非均匀采样的核磁共振波谱重建应用研究》获第五届研究生学术活动月创新成果展二等奖。

[5] 指导的研究生詹嘉莹、涂章仁获得研究生国家奖学金。




 

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