顾运

职称:长聘教轨助理教授

邮箱:yungu@ieee.org

地址:转化医学大楼二楼

最新新闻

- 【TOP】2023年入学的硕士招生目前已经开始,欢迎报名!

【2022/06/30】课题组论文被MICCAI 2022授予Student Travel Award(Top 4%)!

【2022/06/17】课题组论文被IEEE TMI录用!

【2022/06/10】课题组论文获IPCAI2022  Bench-to-Bedside Best Paper Award!

【2022/06/03】课题组论文被MICCAI2022 Early Accept! (Top 13%)!

- 【2022/06/02】课题组论文被IEEE TMI录用!

教育经历

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

科研项目

主持
2021 -  2023  浙江省之江实验室开放课题,“面向大规模医学影像深度模型的预训练与泛化研究”
2021 -  2023  国家自然科学基金-青年科学基金项目,“基于迁移学习的内窥显微成像计算机辅助诊断研究”
2020 -  2022  上海市启明星培育(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  上海脑科学与类脑研究中心,“求索杰出青年”计划
2020 -  2021  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”

参与
2020  -  2022  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 ”

科研成果


【重要期刊】

1.   Y. Gu, C. Gu, J. Yang, J. Sun and G.-Z. Yang, “Vision-Kinematics-Interaction for Robotic-Assisted Bronchoscopy Navigation,” IEEE Transactions on Medical Imaging (TMI), In Press, 2022.

2.   Y. Gu, Y. Xu, J. Yang, W. Xue and G.-Z. Yang, “Towards Robust Feature Embedding for Endomicroscopy Image Classification,” IEEE Transactions on Medical Imaging (TMI), In Press, 2022.

3.   H Zheng, Y Qin, Y. Gu, F Xie, J Yang, J Sun, GZ Yang, “Alleviating class-wise gradient imbalance for pulmonary airway segmentation,” IEEE Transactions on Medical Imaging (TMI), 40(9): 2452-2462, 2021.

4.   Y Qin, H Zheng, Y. Gu, X Huang, J Yang, L Wang, F Yao, YM Zhu, G.Z Yang, “Learning tubule-sensitive CNNs for pulmonary airway and artery-vein segmentation in CT,” IEEE Transactions on Medical Imaging (TMI), 40(6): 1603-1617, 2021

5.   Y. Gu, K. Vyas, M. Shen, J. Yang, and G.-Z. Yang, “Deep Graph-Based Multimodal Feature Embedding for Endomicroscopy Image Retrieval,” IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 32(2): 481-492,2021

6.   Y. Gu and J. Yang, “Densely-Connected Multi-Magnification Hashing for Histopathological Image Retrieval,” IEEE Journal of Biomedical and Health Informatics (JBHI), 23(4): 1683-1691,2019

7.   Y. Gu, K. Vyas, J. Yang, and G.-Z. Yang, “Transfer Recurrent Feature Learning for Endomicroscopy Image Recognition,” IEEE Transactions on Medical Imaging (TMI), 38(3): 791-801, 2019.

8.   Y. Gu, M. Shen, J. Yang, and G.-Z. Yang, “Reliable Label-Efficient Learning for Biomedical Image Recognition,” IEEE Transactions on Biomedical Engineering (TBME), 66(9): 2423-2432, 2019.

9.   Y. Gu, X. Qian, Q. Li, M. Wang, R. Hong, and Q. Tian, “Image annotation by latent community detection and multikernel learning,” IEEE Transactions on Image Processing (TIP), 24(11): 3450-3463, 2015.

 

【重要会议(MICCAI/ICRA/IROS)】

1.   M. Zhang, H. Zhang, G.-Z. Yang, Y. Gu. CFDA: “Collaborative Feature Disentanglement and Augmentation for Pulmonary Airway Tree Modeling of COVID-19 CTs,” International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2022, Early Accepted.

2.   C. Xia, J. Wang, Y. Qin, Y. Gu, B. Chen, J. Yang, “An End-to-End Combinatorial Optimization Method for R-band Chromosome Recognition with Grouping Guided Attention,” International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2022, Early Accepted.

3.   H Zheng, Y Qin, Y. Gu, F Xie, J Sun, J Yang, GZ Yang, “Refined Local-imbalance-based Weight for Airway Segmentation in CT,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2021, pp. 410–419.

4.   C. Zhang, Y. Gu, J. Yang, and G.-Z. Yang, “Diversity-Aware Label Distribution Learning for Microscopy Auto Focusing,” in IEEE International Conference on Robotics and Automation (ICRA) with RAL submission, vol. 6, no. 2, pp. 1942–1949, 2021.

5.   J. Liu, Y. Qiao, J. Yang, G.-Z. Yang, and Y. Gu, “Discriminative Asymmetric Learning for Efficient Surgical Instrument Parsing,” in 2021 IEEE International Conference on Robotics and Automation (ICRA), 2021, pp. 13546–13552.

6.   H. Zhang, Y. Gu, Y. Qin, F. Yao, and G.-Z. Yang, “Learning with sure data for nodule-level lung cancer prediction,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2020, pp. 570–578.

7.   H. Zheng, Z. Zhuang, Y. Qin, Y. Gu, J. Yang, and G.-Z. Yang, “Weakly supervised deep learning for breast cancer segmentation with coarse annotations,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2020, pp. 450–459.

8.   Y Qin, H Zheng, Y. Gu, X Huang, J Yang, L Wang, YM Zhu, “Learning bronchiole-sensitive airway segmentation CNNs by feature recalibration and attention distillation,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2020, pp. 221–231.

9.   M. Shen, Y. Gu, N. Liu, and G.-Z. Yang, “Context-aware depth and pose estimation for bronchoscopic navigation,” in IEEE International Conference on Robotics and Automation (ICRA) with RAL submission, vol. 4, no. 2, pp. 732–739, 2019.

10. Y Qin, M Chen, H Zheng, Y. Gu, M Shen, J Yang, X Huang, YM Zhu, GZ Yang, “Airwaynet: a voxel-connectivity aware approach for accurate airway segmentation using convolutional neural networks,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2019, pp. 212–220.

11. Y. Gu, B. Walter, J. Yang, A. Meining, and G.-Z. Yang, “Triplet Feature Learning on Endoscopic Video Manifold for Online GastroIntestinal Image Retargeting,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2019, pp. 38–46.

12. Y. Gu, K. Vyas, J. Yang, and G.-Z. Yang, “Weakly supervised representation learning for endomicroscopy image analysis,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2018, pp. 326–334.

13. H. Zheng, Y. Gu, Y. Qin, X. Huang, J. Yang, and G.-Z. Yang, “Small lesion classification in dynamic contrast enhancement MRI for breast cancer early detection,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2018, pp. 876–884.

14. Y. Hu, Y. Gu, J. Yang, and G.-Z. Yang, “Multi-stage suture detection for robot assisted anastomosis based on deep learning,” in 2018 IEEE International Conference on Robotics and Automation (ICRA), 2018, pp. 4826–4833.

15. Y. Gu, Y. Hu, L. Zhang, J. Yang, and G.-Z. Yang, “Cross-scene suture thread parsing for robot assisted anastomosis based on joint feature learning,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018, pp. 769–776.

16. Y. Gu, K. Vyas, J. Yang, and G.-Z. Yang, “Unsupervised feature learning for endomicroscopy image retrieval,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2017, pp. 64–71.

17. Y. Gu, C. Ma, and J. Yang, “Supervised recurrent hashing for large scale video retrieval,” in Proceedings of the 24th ACM international conference on Multimedia (ACM MM), 2016, pp. 272–276.



获奖

2019,李介谷优秀博士论文奖

2022,IPCAI Best Bench-to-Bedside Paper Award(第一作者为研一硕士)

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