Lie Ju

PhD Candidate

Monash Medical AI Group (MMAI),
Department of Engineering, Monash University,
eResearch Centre, Monash University,

Email: julie334600@gmail.com & Lie.Ju1@monash.edu

Biography

I am currently a final-year bachelor-straight-to-Ph.D student in Monash Medical AI Group ( MMAI ) at Monash University under the supervision of A/Prof. Zongyuan Ge and Prof. Tom Drummond. I got a bachelor degree at Northwest A&F University in 2019 in China. I'm also an internship in Airdoc, Shanghai. Mrs. Xin Wang and Mr. Xin Zhao are my industrial advisor.

My research interest lies in medical image analysis, long-tailed learning and annotation-efficient learning.

I am on the academic job market for postdoctoral positions in AI for healthcare. Please don’t hesitate to reach out to me if you have any relevant job opportunities.

News

2023. 10. I join UCL as a research visitor, working with Yukun Zhou, Daniel C. Alexander and Pearse A. Keane.

2023. 9. One paper has been accepted by Journal of Big Data (IF: 10.835).

2023. 9. One paper has been accepted by NeurIPS 2023.

2023. 8. One paper has been accepted by IEEE Transactions on Medical Imaging (IF: 11.037).

2023. 6. Three papers have been accepted by MICCAI 2023.

2022. 11. One paper has been accepted by AAAI 2023.

2022. 6. Three papers have been accepted by MICCAI 2022.

2022. 1. One paper has been accepted by IEEE Transactions on Medical Imaging (IF: 11.037).

2021. 8. One paper has been accepted by British Journal of Ophthalmology (IF: 5.907).

2021. 7. Two papers have been accepted by MICCAI 2021.

2021. 3. One paper has been accepted by Information Fusion (IF: 17.564).

2021. 1. One paper has been accepted by IEEE Journal of Biomedical and Health Informatics (IF: 7.021).

2021. 1. One paper has been accepted by IEEE Transactions on Medical Imaging (IF: 11.037).

Selected Publications

	Hierarchical knowledge guided learning for real-world retinal diseases recognition. Lie Ju, Zhen Yu, Lin Wang, Xin Zhao, Xin Wang, Paul Bonnington, Zongyuan Ge IEEE Transactions on Medical Imaging (TMI), 2023. [paper] [code]
	Improving medical image classification with label noise using dual-uncertainty estimation. Lie Ju, Xin Wang, Lin Wang, Dwarikanath Mahapatra, Xin Zhao, Quan Zhou, Tongliang Liu, Zongyuan Ge. IEEE Transactions on Medical Imaging (TMI), 2022. [paper] [datasets]
	Leveraging Regular Fundus Images for Training UWF Fundus Diagnosis Models via Adversarial Learning and Pseudo-Labeling. Lie Ju, Xin Wang, Xin Zhao, Paul Bonnington, Tom Drummond, Zongyuan Ge. IEEE Transactions on Medical Imaging (TMI), 2021. [paper]
	Synergic adversarial label learning for grading retinal diseases via knowledge distillation and multi-task learning. Lie Ju, Xin Wang, Xin Zhao, Huimin Lu, Dwarikanath Mahapatra, Paul Bonnington, Zongyuan Ge. IEEE Journal of Biomedical and Health Informatics (JBHI), 2021. [paper] [code]
	Flexible Sampling for Long-tailed Skin Lesion Classification. Lie Ju, Yicheng Wu, Lin Wang, Zhen Yu, Xin Zhao, Xin Wang, Paul Bonnington, Zongyuan Ge. Medical Image Computing and Computer Assisted Interventions (MICCAI), 2022. [paper] [code]
	Relational Subsets Knowledge Distillation for Long-tailed Retinal Diseases Recognition. Lie Ju, Xin Wang, Lin Wang, Tongliang Liu, Xin Zhao, Tom Drummond, Dwarikanath Mahapatra, Zongyuan Ge. Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021. [paper] [code]
	Medical matting: Medical image segmentation with uncertainty from the matting perspective. Lin Wang, Xiufen Ye, Lie Ju, Wanji He, Donghao Zhang, Xin Wang, Yelin Huang, Wei Feng, Kaimin Song, Zongyuan Ge. Computers in Biology and Medicine (CIBM), 2022. [paper ] [code]
	3D matting: A benchmark study on soft segmentation method for pulmonary nodules applied in computed tomography. Lin Wang, Xiufen Ye, Donghao Zhang, Wanji He, Lie Ju, Yi Luo, Huan Luo, Xin Wang, Wei Feng, Kaimin Song, Xin Zhao, Zongyuan Ge. Computers in Biology and Medicine (CIBM), 2022. [paper] [code]
	Unsupervised Domain Adaptation for Medical Image Segmentation by Selective Entropy Constraints and Adaptive Semantic Alignment. Wei Feng, Lie Ju, Lin Wang, Kaimin Song, Xin Zhao, Zongyuan Ge. AAAI Conference on Artificial Intelligence (AAAI), 2023. [paper] [code]
	Skin Lesion Recognition with Class-Hierarchy Regularized Hyperbolic Embeddings. Zhen Yu, Toan Nguyen, Yaniv Gal, Lie Ju, Shekhar Chandra, Lei Zhang, Paul Bonnington, Victoria Mar, Zhiyong Wang, Zongyuan Ge. Medical Image Computing and Computer Assisted Interventions (MICCAI), 2022. [paper]
	Unsupervised Domain Adaptive Fundus Image Segmentation with Category-level Regularization. Wei Feng, Lin Wang, Lie Ju, Xin Zhao, Xin Wang, Xiaoyu Shi, Zongyuan Ge Medical Image Computing and Computer Assisted Interventions (MICCAI), 2022. [paper] [code]
	Medical Matting: A New Perspective on Medical Segmentation with Uncertainty. Lin Wang, Lie Ju, Donghao Zhang, Xin Wang, Wanji He, Yelin Huang, Zhiwen Yang, Xuan Yao, Xin Zhao, Xiufen Ye, Zongyuan Ge. Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021. [paper] [code]
	Retinal abnormalities recognition using regional multitask learning. Xin Wang, Lie Ju, Xin Zhao, Zongyuan Ge. Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019. [paper]

Professional Activities

Conference Reviews:
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
AAAI Conference on Artificial Intelligence (AAAI)
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
Journal Reviews:
IEEE Transactions on Medical Imaging (TMI)
Medical Image Analysis (MedIA)
IEEE Transactions on Image Processing (TIP)
IEEE Journal of Biomedical and Health Informatics (JBHI)
IEEE Access
Neurocomputing
Computers in Biology and Medicine (CIBM)
Scientific Reports