Junjie Hu

Junjie Hu

Sichuan University

I am currently an associate professor in the College of Computer Science at Sichuan University. I graduated from Sichuan University with a Ph.D. degree under the guidance of professor zhang yi (章毅).

My research interests lie in the field of artificial intelligence and its application in medical domain, with a specific focus on radiotherapy. Detailed research directions include image modality conversion, medical image recognition, and multi-objective inverse optimization in radiotherapy. To date, I have published over 20 papers in international journals . If you are interested in my research, please don’t hesitate to contact me via email at hujunjie@scu.edu.cn.

📝 Publications

  • Song, Ying, Junjie Hu, Zhang Yi, et al. “Young oncologists benefit more than experts from deep learning-based organs-at-risk contouring modeling in nasopharyngeal carcinoma radiotherapy: A multi-institution clinical study exploring working experience and institute group style factor.” Clinical and Translational Radiation Oncology 41 (2023).
  • Wang, Jianyong, Junjie Hu, Ying Song, Qiang Wang, Xiaozhi Zhang, Sen Bai, and Zhang Yi. “VMAT dose prediction in radiotherapy by using progressive refinement UNet.” Neurocomputing 488 (2022): 528-539.
  • Wang, Han, Junjie Hu, Ying Song, Lei Zhang, Sen Bai, and Zhang Yi. “Multi-view fusion segmentation for brain glioma on CT images.” Applied Intelligence (2022): 1-15.
  • Qi, Xiaofeng, Junjie Hu, and Zhang Yi. “Missed diagnoses detection by adversarial learning.” Knowledge-Based Systems 220 (2021): 106903.
  • Xu, Lei, Junjie Hu, Ying Song, Sen Bai, and Zhang Yi. “Clinical target volume segmentation for stomach cancer by stochastic width deep neural network.” Medical Physics 48, no. 4 (2021): 1720-1730.
  • Junjie, Hu, Ying Song, Lei Zhang, Sen Bai, and Zhang Yi. “Multi-scale attention U-net for segmenting clinical target volume in graves’ ophthalmopathy.” Neurocomputing 427 (2021): 74-83.
  • Junjie, Hu, Ying Song, Qiang Wang, Sen Bai, and Zhang Yi. “Incorporating historical sub-optimal deep neural networks for dose prediction in radiotherapy.” Medical Image Analysis 67 (2021): 101886.
  • Wang, Han, Haixian Zhang, Junjie Hu, Ying Song, Sen Bai, and Zhang Yi. “DeepEC: An error correction framework for dose prediction and organ segmentation using deep neural networks.” International Journal of Intelligent Systems 35, no. 12 (2020): 1987-2008.
  • Junjie, Hu, Yuanyuan Chen, Lei Zhang, and Zhang Yi. “Surrogate dropout: Learning optimal drop rate through proxy.” Knowledge-Based Systems 206 (2020): 106340.
  • Qi, Xiaofeng, Junjie Hu, Lei Zhang, Sen Bai, and Zhang Yi. “Automated segmentation of the clinical target volume in the planning CT for breast cancer using deep neural networks.” IEEE Transactions on Cybernetics 52, no. 5 (2020): 3446-3456.
  • Song, Ying, Junjie Hu, Yang Liu, Haiyun Hu, Yang Huang, Sen Bai, and Zhang Yi. “Dose prediction using a deep neural network for accelerated planning of rectal cancer radiotherapy.” Radiotherapy and Oncology 149 (2020): 111-116.
  • Song, Ying, Junjie Hu, Qiang Wu, Feng Xu, Shihong Nie, Yaqin Zhao, Sen Bai, and Zhang Yi. “Automatic delineation of the clinical target volume and organs at risk by deep learning for rectal cancer postoperative radiotherapy.” Radiotherapy and Oncology 145 (2020): 186-192.
  • He, Tao, Junjie Hu, Ying Song, Jixiang Guo, and Zhang Yi. “Multi-task learning for the segmentation of organs at risk with label dependence.” Medical Image Analysis 61 (2020): 101666.
  • Hu, Wang, Yu Zhang, Junjie Hu, Yan Qi, and Guoming Lu. “A Fast Particle Swarm Optimization Algorithm by Refining the Global Best Solution.” In Proceedings of the 2020 2nd Asia Pacific Information Technology Conference, pp. 128-135. 2020.
  • Wu, Bolin, Wang Hu, Junjie Hu, and Gary G. Yen. “Adaptive multiobjective particle swarm optimization based on evolutionary state estimation.” IEEE Transactions on Cybernetics 51, no. 7 (2019): 3738-3751.
  • Huang, Yueyao, and Junjie Hu. “Residual neural network based classification of macular edema in oct.” In 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), pp. 736-743. IEEE, 2019.
  • Zhang, Wei, Jie Zhong, Shijun Yang, Zhentao Gao, Junjie Hu, Yuanyuan Chen, and Zhang Yi. “Automated identification and grading system of diabetic retinopathy using deep neural networks.” Knowledge-Based Systems 175 (2019): 12-25.
  • Junjie, Hu, Yuanyuan Chen, and Zhang Yi. “Automated segmentation of macular edema in OCT using deep neural networks.” Medical image analysis 55 (2019): 216-227.
  • Wang, Jianyong, Rong Ju, Yuanyuan Chen, Lei Zhang, Junjie Hu, Yu Wu, Wentao Dong, Jie Zhong, and Zhang Yi. “Automated retinopathy of prematurity screening using deep neural networks.” EBioMedicine 35 (2018): 361-368.
  • Junjie, Hu, Yuanyuan Chen, Jie Zhong, Rong Ju, and Zhang Yi. “Automated analysis for retinopathy of prematurity by deep neural networks.” IEEE transactions on medical imaging 38, no. 1 (2018): 269-279.

💻 Projects

  • Host National Natural Science Youth Foundation of China. (主持国家自然科学青年基金)
  • Host Postdoctoral Science Foundation of China. (主持中国博士后面上项目)
  • Host Postdoctoral Science Foundation of Sichuan University. (主持四川大学博士后基金)

🎖 Honors and Awards

  • 2022 Second Prize of Sichuan Province Medical Science and Technology for Young. (2022年四川省医学青年科技二等奖)
  • 2019 National College Artificial Intelligence Innovation Competition, First Prize. (2019年中国人工智能创新大赛, 一等奖)
  • 2018 AI Challenge of Automated Macular Edema Recognition, Second Prize. (2018年全球AI挑战赛, 黄斑水肿病变分割比赛, 二等奖)

📖 Educations

  • 2021.01 - now, Sichuan Univeristy, Associate Professor.
  • 2016.09 - 2020.12, Sichuan Univeristy, PhD.
  • 2013.09 - 2016.07, University of Electronic Science and Technology of China, Master.
  • 2009.09 - 2013.07, Chengdu University of Technology, Bachelor.