Publications

This is home for my research publications, each linked with
accompanying preprints, posters, and/or news pieces.

VAP-Diffusion: Enriching Descriptions with MLLMs for Enhanced Medical Image Generation

A novel diffusion-based approach for medical image generation using MLLM-enriched descriptions.

2025

Peng Huang, Junhu Fu, Bowen Guo, Zeju Li, Yuanyuan Wang, Yi Guo

FedFDD: Federated Learning with Frequency Domain Decomposition for Low-Dose CT Denoising

A federated learning approach with frequency domain decomposition for low-dose CT denoising.

2024

Xuhang Chen, Zeju Li, Zikun Xu, Kaijie Xu, Cheng Ouyang, Chen Qin

Post-Deployment Adaptation with Access to Source Data via Federated Learning and Source-Target Remote Gradient Alignment

A federated learning approach for post-deployment adaptation with source-target remote gradient alignment.

2023

MICCAI-MLMI 2023

Felix Wagner, Zeju Li, Pramit Saha, Konstantinos Kamnitsas

Robust Segmentation via Topology Violation Detection and Feature Synthesis

A novel approach for robust segmentation using topology violation detection and feature synthesis.

2023

Liu Li, Qiang Ma, Cheng Ouyang, Zeju Li, Qingjie Meng, Weitong Zhang, Mengyun Qiao, Vanessa Kyriakopoulou, Joseph Hajnal, Daniel Rueckert, Bernhard Kainz

Robustness Stress Testing in Medical Image Classification

A comprehensive approach for robustness stress testing in medical image classification.

2023

MICCAI-UNSURE 2023

Mobarakol Islam, Zeju Li, Ben Glocker

Context Label Learning: Improving Background Class Representations in Semantic Segmentation

A novel approach for improving background class representations in semantic segmentation through context label learning.

highlights

2023

IEEE Transactions on Medical Imaging

Zeju Li, Konstantinos Kamnitsas, Cheng Ouyang, Chen Chen, Ben Glocker

Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in Segmentation

A novel approach for joint optimization of class-specific training and test-time data augmentation in medical image segmentation tasks.

highlights

2023

IEEE Transactions on Medical Imaging

Zeju Li, Konstantinos Kamnitsas, Qi Dou, Chen Qin, Ben Glocker

Causality-inspired Single-source Domain Generalization for Medical Image Segmentation

A causality-inspired approach for single-source domain generalization in medical image segmentation.

2022

IEEE Transactions on Medical Imaging

Cheng Ouyang, Chen Chen, Surui Li, Zeju Li, Chen Qin, Wenjia Bai, Daniel Rueckert

Tackling Long-Tailed Category Distribution Under Domain Shifts

A novel approach for handling long-tailed category distribution under domain shifts in medical imaging.

2022

Xiao Gu, Yao Guo, Zeju Li, Jianning Qiu, Qi Dou, Yuxuan Liu, Benny Lo, Guang-Zhong Yang

Estimating Model Performance under Domain Shifts with Class-Specific Confidence Scores

A novel approach for estimating model performance under domain shifts using class-specific confidence scores.

highlights

2022

Zeju Li, Konstantinos Kamnitsas, Mobarakol Islam, Chen Chen, Ben Glocker

Fetal Cortex Segmentation with Topology and Thickness Loss Constraints

A novel approach for fetal cortex segmentation using topology and thickness loss constraints.

2022

MICCAI-TDA 2022

Liu Li, Qiang Ma, Zeju Li, Cheng Ouyang, Weitong Zhang, Anthony Price, Vanessa Kyriakopoulou, Lucilio Cordero-Grande, Antonis Makropoulos, Joseph Hajnal, Daniel Rueckert, Bernhard Kainz, Amir Alansary

Improved Post-Hoc Probability Calibration for Artifact-Corrupted MRI Segmentation

An improved post-hoc probability calibration approach for artifact-corrupted MRI segmentation.

2022

MICCAI-UNSURE 2022

Cheng Ouyang, Shuo Wang, Chen Chen, Zeju Li, Wenjia Bai, Bernhard Kainz, Daniel Rueckert

MaxStyle: Adversarial Style Composition for Robust Medical Image Segmentation

An adversarial style composition approach for robust medical image segmentation.

2022

Chen Chen, Zeju Li, Cheng Ouyang, Matt Sinclair, Wenjia Bai, Daniel Rueckert

Enhancing MR Image Segmentation with Realistic Adversarial Data Augmentation

A novel approach for enhancing MR image segmentation through realistic adversarial data augmentation techniques.

2022

Medical Image Analysis

Chen Chen, Cheng Ouyang, Zeju Li, Shuo Wang, Huaqi Qiu, Liang Chen, Giacomo Tarroni, Wenjia Bai, Daniel Rueckert

Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning

A comprehensive multi-task medical image registration challenge with standardized evaluation framework.

2022

IEEE Transactions on Medical Imaging

Alessa Hering, Lasse Hansen, Tony CW Mok, Albert CS Chung, Hanna Siebert, Stephanie Häger, Annkristin Lange, Sven Kuckertz, Stefan Heldmann, Wei Shao, others

Breast Tumor Classification based on MRI-US Images by Disentangling Modality Features

A novel multi-modal approach for breast tumor classification using MRI and ultrasound images with modality feature disentanglement.

2022

IEEE Journal of Biomedical and Health Informatics

Mengyun Qiao, Chengcheng Liu, Zeju Li, Jin Zhou, Qin Xiao, Shichong Zhou, Cai Chang, Gu Yajia, Yi Guo, Yuanyuan Wang

Federated Deep Learning for Detecting COVID-19 Lung Abnormalities in CT: A Privacy-Preserving Multinational Validation Study

A privacy-preserving federated learning approach for detecting COVID-19 lung abnormalities across multiple institutions.

2021

NPJ Digital Medicine

Qi Dou, Tiffany Y So, Meirui Jiang, Quande Liu, Varut Vardhanabhuti, Georgios Kaissis, Zeju Li, Weixin Si, Heather HC Lee, Kevin Yu, others

A Novel Image Signature-Based Radiomics Method to Achieve Precise Diagnosis and Prognostic Stratification of Gliomas

A novel radiomics approach using image signatures for precise glioma diagnosis and prognostic stratification.

2021

Laboratory Investigation

Huigao Luo, Qiyuan Zhuang, Yuanyuan Wang, Aibaidula Abudumijiti, Kuangyu Shi, Axel Rominger, Hong Chen, Zhong Yang, Vanessa Tran, Guoqing Wu, others

Analyzing Overfitting under Class Imbalance in Neural Networks for Image Segmentation

A comprehensive analysis of overfitting behavior in neural networks under class imbalance conditions for medical image segmentation.

highlights

2020

IEEE Transactions on Medical Imaging

Zeju Li, Konstantinos Kamnitsas, Ben Glocker

High-Resolution Chest X-ray Bone Suppression Using Unpaired CT Structural Priors

A novel approach for high-resolution chest X-ray bone suppression using unpaired CT structural priors.

2020

IEEE Transactions on Medical Imaging

Han Li, Hu Han, Zeju Li, Lei Wang, Zhe Wu, Jingjing Lu, S Kevin Zhou

DeepVolume: Brain Structure and Spatial Connection-Aware Network for Brain MRI Super-Resolution

A novel deep learning approach for brain MRI super-resolution that incorporates brain structure and spatial connection awareness.

highlights

2019

IEEE Transactions on Cybernetics

Zeju Li, Jinhua Yu, Yuanyuan Wang, Hanzhang Zhou, Haowei Yang, Zhuowei Qiao

Encoding CT Anatomy Knowledge for Unpaired Chest X-ray Image Decomposition

A novel approach for encoding CT anatomy knowledge to guide unpaired chest X-ray image decomposition.

highlights

2019

Zeju Li, Han Li, Hu Han, Gonglei Shi, Jiannan Wang, Shaohua Kervin Zhou

Overfitting of Neural Nets Under Class Imbalance: Analysis and Improvements for Segmentation

Analysis and improvements for overfitting under class imbalance in neural networks for medical image segmentation.

2019

Zeju Li, Konstantinos Kamnitsas, Ben Glocker

Early Identification of Ischemic Stroke in Noncontrast Computed Tomography

A novel approach for early identification of ischemic stroke in noncontrast CT images.

2019

Biomedical Signal Processing and Control

Guoqing Wu, Jixian Lin, Xi Chen, Zeju Li, Yuanyuan Wang, Jing Zhao, Jinhua Yu

Deep Generative Adversarial Networks for Thinsection Infant MR Image Reconstruction

A novel GAN-based approach for reconstructing high-quality infant MR images from thin-section scans.

2019

Jiaqi Gu, Zeju Li, Yuanyuan Wang, Haowei Yang, Zhongwei Qiao, Jinhua Yu

Super-Resolution Reconstruction of Plane-Wave Ultrasound Image Based on a Multi-Angle Parallel U-Net with Maxout Unit and Novel Loss Function

A novel multi-angle parallel U-Net approach with maxout units for ultrasound image super-resolution reconstruction.

2019

Journal of Medical Imaging and Health Informatics

Zixia Zhou, Yuanyuan Wang, Jinhua Yu, Wei Guo, Zeju Li

Primary Central Nervous System Lymphoma and Glioblastoma Differentiation Based on Conventional Magnetic Resonance Imaging by High-Throughput SIFT Features

A high-throughput SIFT feature-based approach for differentiating primary CNS lymphoma from glioblastoma using conventional MRI.

2018

International Journal of Neuroscience

Yinsheng Chen, Zeju Li, Guoqing Wu, Jinhua Yu, Yuanyuan Wang, Xiaofei Lv, Xue Ju, Zhongping Chen

Left Ventricle Segmentation via Optical-Flow-Net from Short-Axis Cine MRI: Preserving the Temporal Coherence of Cardiac Motion

A novel optical-flow-based approach for left ventricle segmentation preserving temporal coherence in cardiac MRI.

2018

Wenjun Yan, Yuanyuan Wang, Zeju Li, Rob J van der Geest, Qian Tao

A Multi-Scope Convolutional Neural Network for Automatic Left Ventricle Segmentation from Magnetic Resonance Images: Deep-Learning at Multiple Scopes

A multi-scope convolutional neural network approach for automatic left ventricle segmentation from MRI.

2018

Xinyi Li, Yuanyuan Wang, Wenjun Yan, Rob J Van der Geest, Zeju Li, Qian Tao

Primary Central Nervous System Lymphoma and Glioblastoma Image Differentiation Based on Sparse Representation System

A sparse representation-based system for differentiating primary CNS lymphoma from glioblastoma using brain MRI.

2018

Journal of Biomedical Engineering

Guoqing Wu, Zeju Li, Yuanyuan Wang, Jinhua Yu, Yinsheng Chen, Zhongping Chen

Deep Learning based Radiomics (DLR) and its Usage in Noninvasive IDH1 Prediction for Low Grade Glioma

A novel deep learning radiomics approach for noninvasive prediction of IDH1 mutation status in low-grade gliomas.

2017

Scientific Reports

Zeju Li, Yuanyuan Wang, Jinhua Yu, Yi Guo, Wei Cao

Noninvasive IDH1 Mutation Estimation Based on a Quantitative Radiomics Approach for Grade II Glioma

A quantitative radiomics approach for noninvasive estimation of IDH1 mutation status in grade II gliomas.

2017

European Radiology

Jinhua Yu, Zhifeng Shi, Yuxi Lian, Zeju Li, Tongtong Liu, Yuan Gao, Yuanyuan Wang, Liang Chen, Ying Mao

Low-Grade Glioma Segmentation Based on CNN with Fully Connected CRF

A novel CNN-based approach with fully connected CRF for accurate low-grade glioma segmentation in brain MRI.

2017

Journal of Healthcare Engineering

Zeju Li, Yuanyuan Wang, Jinhua Yu, Zhifeng Shi, Yi Guo, Liang Chen, Ying Mao

Age Groups Related Glioblastoma Study Based on Radiomics Approach

A radiomics-based study investigating age-related differences in glioblastoma characteristics and outcomes.

2017

Computer Assisted Surgery

Zeju Li, Yuanyuan Wang, Jinhua Yu, Yi Guo, Qi Zhang

Brain Tumor Segmentation Using an Adversarial Network

A novel adversarial network approach for brain tumor segmentation in MRI.

2017

MICCAI-Brainlesion 2017

Zeju Li, Yuanyuan Wang, Jinhua Yu

Reconstruction of Thin-Slice Medical Images Using Generative Adversarial Network

A generative adversarial network approach for reconstructing high-quality thin-slice medical images.

2017

MICCAI-MLMI 2017

Zeju Li, Yuanyuan Wang, Jinhua Yu