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顾运

助理教授

办公电话: 19921973640
通讯地址: 转化医学大楼二楼
电子邮件: yungu@ieee.org
个人主页: https://geronsushi.github.io

  • 教育背景

    2015 - 2019 上海交通大学,生物医学工程学院,获博士学位
    2016 - 2018 Imperial College London, The Hamlyn Centre, 联合培养博士
    2013 - 2015 上海交通大学,自动化系,获硕士学位
    2009 - 2013 西安交通大学,自动化系,获学士学位

  • 工作经历

    2020至今 上海交通大学,自动化系/医疗机器人研究院,助理教授

  • 研究方向

    医学影像分析,计算机视觉,机器学习

  • 科研项目

    1. 上海市青年科技英才扬帆计划,“基于多模态关联学习的智能数字病理诊断研究”,2020-2022,主持
    2. 上海脑科学与类脑研究中心,“求索杰出青年”计划,2020-2022,主持
    3. 中国计算机学会-腾讯犀牛鸟创意基金,“基于单样本跨模态嵌入的医学影像分类算法研究”,2020-2021,主持
    4. 国家重点研发项目,“面向消化道早癌的诊疗一体化手术机器人关键 技术及系统 ”,2020-2022,参与

  • 代表性论文专著

    1. Hao Zheng, Zhiguo Zhuang, Yulei Qin, Yun Gu*, Jie Yang, Guang-Zhong Yang, Weakly Supervised Deep Learning for Breast Cancer Segmentation with Coarse Annotations, MICCAI, 2020.
    2. Yulei Qin, Hao Zheng, Yun Gu*, Xiaolin Huang, Jie Yang, Lihui Wang, Yuemin Zhu, Learning Bronchiole-Sensitive Airway Segmentation CNNs by Feature Recalibration and Attention Distillation, MICCAI, 2020.
    3. Hao Zheng, Lijun Qian, Yulei Qin, Yun Gu*, Jie Yang, Improving the Slice Interaction of 2.5D CNN for Automatic Pancreas Segmentation, Medical Physics, 2020.
    4. Yulei Qin, Yun Gu*, Hao Zheng, Mingjian Chen, Jie Yang, Yuemin Zhu, AirwayNet-SE: A Simple-yet-Effective Approach to Improve Airway Segmentation Using Context Scale Fusion, ISBI, 2020.
    5. Yun Gu, Khushi Vyas, Jie Yang, Guang-Zhong Yang Deep Graph-based Multimodal Feature Embedding for Endomicroscopy Image Retrieval, IEEE Transactions on Neural Networks and Learning Systems, 2020.
    6. Yun Gu, Benjamin Walter, Jie Yang, Alexander Meining, Guang-Zhong Yang Triplet Feature Learning on Endoscopic Video Manifold for Real-time Gastrointestinal Image Retargeting, MICCAI, 2019.
    7. Yun Gu, Jie Yang, Multi-level Magnification Correlation Hashing for Scalable Histopathological Image Retrieval, Neurocomputing, 2019.
    8. Yun Gu, Mali Shen, Jie Yang and Guang-Zhong Yang, Reliable Label Efficient Learning for Biomedical Image Recognition, IEEE Transactions on Biomedical Engineering, 2019.
    9. Yun Gu, Jie Yang, Densely-Connected Multi-Magnification Hashing for Histopathological Image Retrieval, IEEE Journal of Biomedical and Health Informatics, 2018.
    10. Yun Gu, Khushi Vyas, Jie Yang and Guang-Zhong Yang, Transfer Recurrent Feature Learning for Endomicroscopy Image Classification, IEEE Transactions on Medical Imaging, 2018.
    11. Yun Gu, Yang Hu, Lin Zhang, Jie Yang and Guang-Zhong Yang, Cross-scene Suture Thread Parsing for Robot Assisted Anastomosis based on Joint Representation Learning, IEEE IROS, 2018.
    12. Yun Gu, Khushi Vyas, Jie Yang and Guang-Zhong Yang, Weakly-supervised Reperesentation Learning for Endomicroscopy Image Analysis, MICCAI, 2018 (Student Travel Award).
    13. Yun Gu, Khushi Vyas, Jie Yang and Guang-Zhong Yang, Unsupervised Feature Learning for Endomicroscopy Image Retrieval, MICCAI, 2017.
    14. Yun Gu, Chao Ma, Jie Yang, Supervised Recurrent Hashing for Large Scale Video Retrieval, ACM Multimedia, 2016.
    15. Yun Gu, Guang-Zhong Yang, Jie Yang, Multi-View Multi-Model Embedding for Endomicroscopy Mosaics Classification,IEEE CVPR Workshop on Computer Vision for Microscopy Image Analysis, 2016.
    16. Yun Gu, Haoyang Xue, Jie Yang et.al ,Cross-modal Saliency Correlation for Image Annotation,Neural Processing Letters, 2016.
    17. Yun Gu, Xueming Qian, Qing Li et.al ,Image Annotation by Latent Community Detection and Multiple Kernel Learning, IEEE Transactions on Image Processing, 2015.
    18. Yun Gu, Haoyang Xue, Jie Yang, et.al. Cross-modality Hashing with Partial Correspondence. in IEEE International Conference on Image Processing (ICIP,Oral), 2015.
    19. Yun Gu, Haoyang Xue, Jie Yang, et.al.Automatic Image Annotation Exploiting Visual and Textual Saliency, in 21st International Conference on Neural Information Processing (ICONIP,Oral), 2014.
    20. Yun Gu, Ting Liu, Dai Wang, Xiaohong Guan and Zhanbo Xu,Bad Data Detection Method for Smart Grid Based on Distributed State Estimation", in IEEE International Conference on Communications (ICC), 2013.
    21. Tianyi Zhang, Yun Gu, Xiaolin Huang, Enmei Tu, Jie Yang, Stereo Endoscopic Image Super-Resolution Using Disparity-Constrained Parallel Attention, AI4AH, ICLR, 2020.
    22. Mali Shen*,Yun Gu*, Ning Liu and Guang-Zhong Yang, Context-Aware Depth and Pose Estimation for Bronchoscopic Navigatio, IEEE Robotics and Automation Letters, 2018 (Equal Contribution).
    23. Mali Shen*,Yun Gu*, Pallav Shah and Guang-Zhong Yang, Unsupervised Learning of Depth Estimation from Video for Bronchoscopic Navigation, Hamlyn Symposium for Medical Robots, 2018 (Equal Contribution, Oral).
    24. Hao Zheng, Yun Gu, Yulei Qin, Xiaolin Huang, Jie Yang and Guang-Zhong Yang, Small Lesion Classification in Dynamic Contrast Enhancement MRI for Breast Cancer Early Detection, MICCAI, 2018.
    25. Yang Hu*, Yun Gu*, Jie Yang and Guang-Zhong Yang, Deep Multi-Stage Detection for Surgical Suture Threads, IEEE ICRA, 2018 (Equal Contribution).
    26. Chao Ma, Yun Gu, Jie Yang, Unsupervised Video Hashing by Exploiting Spatial-Temporal Feature, ICONIP, 2016.
    27. Yun Gu, Guang-Zhong Yang, Jie Yang and Kun Sun, 4D Cardiac Ultrasound Standard Plane Location by Spatial-Temporal Correlation, Technical Report, 2016.
    28. Liqun Ji, Yun Gu, Kun Sun, Jie Yang, Yu Qiao, Congenital Heart Disease (CHD) Discrimination in Fetal Echocardiogram based on 3D Feature Fusion, IEEE International Conference on Image Processing (ICIP), 2016.
    29. Qiuxing Chen, Yun Gu, Lixiu Yao, et.al. Pedestrian Counting with Random Forests. in 22nd International Conference on Neural Information Processing (ICONIP), 2015.
    30. Shuai Huang, Yun Gu, Jie Yang, et.al. Reranking of Person Re-identification by Manifold-based approach. in IEEE International Conference on Image Processing (ICIP), 2015.
    31. Haoyang Xue, Yun Gu, Jie Yang, et.al. RGB-D Saliency Detection via Mutual Guided Manifold Ranking. in IEEE International Conference on Image Processing (ICIP), 2015.
    32. Qing Li, Yun Gu and Xueming Qian. LCMKL: Latent-community and multi-kernel learning based image annotation,in ACM International Conference on Information and Knowledge Management (CIKM), 2013.
    33. Ting Liu, Yun Gu, Dai Wang and Yuhong Gui. APSE: A Novel Method to Detect Bad Data Injection Attack in Smart Grid".in IEEE INFOCOM, 2013.

  • 荣誉奖励

    2019,李介谷优秀博士论文奖

友情链接
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医疗机器人研究院