Zeju Li  

Ph.D. Student

Department of Computing,
Imperial College London,
South Kensington, London, UK.

 
Email zeju.li18(at)imperial.ac.uk
Curriculum Vitae

Zeju Li is currently a Ph.D. student from the Department of Computing, Imperial College London under the supervision of Dr. Ben Glocker.
Previously, he got both his M.S. and B.S. from the Department of Electronic Engineering, Fudan University separately in 2018 and 2015, under the supervision of Prof. Yuanyuan Wang, where he also worked very closely with Prof. Jinhua Yu. He interned at Chinese Academy of Sciences working with Prof. Shaohua Kevin Zhou and Dr. Hu Han.

His personal social websites are Linkedin | Twitter | Github.

Zeju Li is boardly interested in medical image computing, computer vision and machine learning. Currently, Zeju Li is working on improving the generalization capability of neural networks for medical imaging.


Updates:
Selected Publications (Google Scholar)

Analyzing Overfitting under Class Imbalance in Neural Networks for Image Segmentation,
Zeju Li, Konstantinos Kamnitsas, Ben Glocker.
IEEE Transactions on Medical Imaging, 2020.

[Paper][Supp][Code]

High-Resolution Chest X-ray Bone Suppression Using Unpaired CT Structural Priors,
Han Li, Hu Han, Zeju Li, Lei Wang, Zhe Wu, Jingjing Lu, S. Kevin Zhou.
IEEE Transactions on Medical Imaging, 2020.

[Paper]

DeepVolume: Brain Structure and Spatial Connection-Aware Network for Brain MRI Super-Resolution,
Zeju Li, Jinhua Yu, Yuanyuan Wang, Hanzhang Zhou, Haowei Yang, Zhongwei Qiao.
IEEE Transactions on Cybernetics, 2019.

[Paper][Code]

Overfitting of neural nets under class imbalance: Analysis and improvements for segmentation,
Zeju Li, Konstantinos Kamnitsas, Ben Glocker.
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019.

[Paper][Code]

Encoding CT Anatomy Knowledge for Unpaired Chest X-ray Image Decomposition,
Zeju Li, Han Li, Hu Han, Gonglei Shi, Jiannan Wang, S. Kevin Zhou.
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019.

[Paper][Code]

Deep Generative Adversarial Networks for Thinsection Infant MR Image Reconstruction,
Jiaqi Gu, Zeju Li, Yuanyuan Wang, Haowei Yang, Zhongwei Qiao, Jinhua Yu.
IEEE Access, 2019.

[Paper]

Left Ventricle Segmentation via Optical-Flow-Net from Short-Axis Cine MRI: Preserving the Temporal Coherence of Cardiac Motion,
Wenjun Yan, Yuanyuan Wang, Zeju Li, Rob J. van der Geest, Qian Tao.
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018.

[Paper]

Deep learning based radiomics (DLR) and its usage in noninvasive IDH1 prediction for low grade glioma,
Zeju Li, Yuanyuan Wang, Jinhua Yu, Yi Guo and Wei Cao.
Scientific Reports, 2017.

[Paper]

Low-grade glioma segmentation based on CNN with fully connected CRF,
Zeju Li, Yuanyuan Wang, Jinhua Yu, Zhifeng Shi, Yi Guo, Liang Chen, Ying Mao.
Journal of Healthcare Engineering, 2017.

[Paper]

Noninvasive IDH1 mutation estimation based on a quantitative radiomics approach for grade II glioma,
Jinhua Yu, Zhifeng Shi, Yuxi Lian, Zeju Li, Tongtong Liu, Yuan Gao, Yuanyuan Wang, Liang Chen, Ying Mao.
European Radiology, 2017.

[Paper]


Awards and Honors

Academic Service

Teaching Experience

MorroBay
Other Interests

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