• [07/2025] One paper was accepted by TMI.
• [06/2025] Three papers were accepted by MICCAI 2025.
• [06/2025] One paper was accepted by Neural Networks.
• [06/2025] Invited to serve as Area Chair of AAAI 2026.
• [05/2025] One paper was accepted by TPAMI.
• [05/2025] One paper was accepted by TPAMI.
• [05/2025] One paper was accepted to ACL 2025.
• [05/2025] Two papers were accepted by ICML 2025.
• [04/2025] Invited to be an Associate Editor of npj Digital Medicine.
• [04/2025] Invited to serve as Area Chair of NeurIPS 2025.
• [04/2025] The 3rd Workshop on Computer Vision for Automated Medical Diagnosis will appear in ICCV 2025.
• [02/2025] The 2nd tutorial on GraphMedIA: Graph Learning in Medical Image Analysis will appear in MICCAI 2025.
• [02/2025] One paper was accepted by TMI.
• [12/2024] One paper was accepted by npj Digital Medicine.
• [12/2024] Two papers were accepted by AAAI 2025.
• [10/2024] One paper was accepted by TMI.
• [09/2024] One paper was accepted by NeurIPS 2024.
• [09/2024] One paper was accepted by TPAMI.
• [08/2023] Recent publications in 2024 Summer: 1 MedIA, 1 NN, 1 JBHI, 2 ECCV.
• [06/2024] Three papers were accepted by MICCAI 2024.
• [02/2024] One paper was accepted by CVPR 2024.
• [01/2024] Invited to serve as Area Chair in MICCAI 2024.
• [12/2023] Two papers were accepted by AAAI 2024.
• [09/2023] Two papers were accepted by NeurIPS 2023.
• [07/2023] Recent publications in 2023 Summer: 1 TPAMI, 2 TMI, 1 TIP, 1 JBHI, 1 ICCV, 5 MICCAI.
• [04/2023] One co-authored paper was accepted by Radiology: Artificial Intelligence.
• [03/2023] Three papers were accepted by CVPR 2023.
• [01/2023] Invited to serve as Area Chair in MICCAI 2023.
• [11/2022] One co-authored paper was accepted by Nature Communications.
• [10/2022] Ranked Top 2% of Scientists on Stanford List.
• [09/2022] Our MICCAI CMMCA workshop paper got the Best Paper Award.
• [09/2022] Our MICCAI DART workshop paper got the Best Paper Honorable Mention Award.
• [04/2022] Named on the World's First List of Top 150 Chinese Young Scholars in Artificial Intelligence.

Experience

• Stanford University, Palo Alto, California, USA
  Nov. 2019 – Mar. 2021
  
  Postdoctoral Research Fellow
  Advisor: Prof. Lei Xing
  
• NVIDIA, deep learning for medical imaging research group, Bethesda, Maryland, USA
  Jul. 2018 – Oct. 2018
  
  Applied Research Intern
  Topic: Few-shot medical image segmentation
  
• Siemens Healthineers, Princeton, New Jersey, USA
  Mar. 2017 – Jul. 2017
  
  Research Intern
  Topic: Body landmark detection via deep reinforcement learning
  

Selected Publications [Google Scholar]

2025

• Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior
  Tsai Hor Chan, Dora Yan Zhang, Guosheng Yin, Lequan Yu.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025.
  
• Scaling Chest X-ray Foundation Models from Mixed Supervisions for Dense Prediction
  Fuying Wang, Lequan Yu.
  IEEE Transactions on Medical Imaging (TMI), 2025.
  
• MoST-IG: Morphology-Guided Spatial Transcriptomics Integration via Visual-Genomic Graph Optimal Transport
  Liting Yu, Tao Ma, Weiqin Zhao, Zhuo Liang, Lequan Yu.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2025.
  
• HyperPath: Knowledge-Guided Hyperbolic Semantic Hierarchy Modeling for WSI Analysis
  Peixiang Huang, Yanyan Huang, Weiqin Zhao, Junjun He, Lequan Yu.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2025.
  
• Bridging Radiological Images and Factors with Vision-Language Model for Accurate Diagnosis of Proliferative Hepatocellular Carcinoma
  Yanyan Huang, Wanli Zhang, Peixiang Huang, Yu Fu, Ruimeng Yang, Lequan Yu.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2025.
  
• Democratizing Large Language Model-Based Graph Data Augmentation via Latent Knowledge Graphs
  Yushi Feng, Tsai Hor Chan, Guosheng Yin, Lequan Yu.
  Neural Networks, 2025.
  
• CTPD: Cross-Modal Temporal Pattern Discovery for Enhanced Multimodal Electronic Health Records Analysis
  Fuying Wang, Feng Wu, Yihan Tang, Lequan Yu.
  Annual Meeting of the Association for Computational Linguistics (ACL), 2025.
  
• From Token to Rhythm: A Multi-Scale Approach for ECG-Language Pretraining
  Fuying Wang, Jiacheng Xu, Lequan Yu.
  International Conference on Machine Learning (ICML), 2025.
  
• Cross-Modal Alignment via Variational Copula Modelling
  Feng Wu, Tsai Hor Chan, Fuying Wang, Guosheng Yin, Lequan Yu.
  International Conference on Machine Learning (ICML), 2025.
  

[code]

• TAD-Graph: Enhancing Whole Slide Image Analysis via Task-Aware Subgraph Disentanglement
  Fuying Wang, Jiayi Xin, Weiqin Zhao, Yuming Jiang, Maximus Yeung, Liansheng Wang, Lequan Yu.
  IEEE Transactions on Medical Imaging (TMI), 2025.
  

[code]

• Large Images are Gaussians: High-Quality Large Image Representation with Levels of 2D Gaussian Splatting
  Lingting Zhu, Guying Lin, Jinnan Chen, Xinjie Zhang, Zhenchao Jin, Zhao Wang, Lequan Yu.
  AAAI Conference on Artificial Intelligence (AAAI), 2025.
  

[code]

• From Layers to States: A State Space Model Perspective to Deep Neural Network Layer Dynamics
  Qinshuo Liu, Weiqin Zhao, Wei Huang, Yanwen Fang, Lequan Yu, Guodong Li.
  International Conference on Learning Representations (ICLR), 2025.
  

2024

• Aligning Knowledge Concepts to Whole Slide Images for Precise Histopathology Image Analysis
  Weiqin Zhao, Ziyu Guo, Yinshuang Fan, Yuming Jiang, Maximus Yeung, Lequan Yu.
  npj Digital Medicine, 2024.
  

[code]

• Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement
  Yanyan Huang, Weiqin Zhao, Yihang Chen, Yu Fu, Lequan Yu.
  Conference on Neural Information Processing Systems (NeurIPS), 2024.
  

[code]

• Unleash the Power of State Space Model for Whole Slide Image with Local Aware Scanning and Importance Resampling
  Yanyan Huang, Weiqin Zhao, Yu Fu, Lingting Zhu, Lequan Yu.
  IEEE Transactions on Medical Imaging (TMI), 2024.
  

[code]

• Multi-sensor Learning Enables Information Transfer across Different Sensory Data and Augments Multi-modality Imaging
  Lingting Zhu, Yizheng Chen, Lianli Liu, Lei Xing, Lequan Yu.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
  

[code]

• HERGen: Elevating Radiology Report Generation with Longitudinal Data
  Fuying Wang, Shenghui Du, Lequan Yu.
  European Conference on Computer Vision (ECCV), 2024.
  

[code]

• cDP-MIL: Robust Multiple Instance Learning via Cascaded Dirichlet Process
  Yihang Chen, Tsai Hor Chan, Guosheng Yin, Yuming Jiang, Lequan Yu.
  European Conference on Computer Vision (ECCV), 2024.
  

[code]

• Multi-task Heterogeneous Graph Learning on Electronic Health Records
  Tsai Hor Chan, Guosheng Yin, Kyongtae Bae, Lequan Yu.
  Neural Networks, 2024.
  

[code]

• Swin-UMamba: Mamba-based UNet with ImageNet-based pretraining
  Jiarun Liu, Hao Yang, Hong-Yu Zhou, Yan Xi, Lequan Yu, Yizhou Yu, Yong Liang, Guangming Shi, Shaoting Zhang, Hairong Zheng, Shanshan Wang.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024.
  

[code]

• ORCGT: Ollivier-Ricci Curvature-based Graph Model for Lung STAS Prediction
  Min Cen, Zheng Wang, Zhenfeng Zhuang, Hong Zhang, Dan Su, Zhen Bao, Weiwei Wei, Baptiste Magnier, Lequan Yu, Liansheng Wang.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024.
  
• Advancing H&E-to-IHC Virtual Staining with Task-Specific Domain Knowledge for HER2 Scoring
  Qiong Peng, Weiping Lin, Yihuang Hu, Ailisi Bao, Chenyu Lian, Weiwei Wei, Meng Yue, Jingxin Liu, Lequan Yu, Liansheng Wang.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024.
  
• L2B: Learning to Bootstrap Robust Models for Combating Label Noise
  Yuyin Zhou, Xianhang Li, Fengze Liu, Qingyue Wei, Xuxi Chen, Lequan Yu, Cihang Xie, Matthew P. Lungren, Lei Xing.
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
  

[code]

• A Dual Enrichment Synergistic Strategy to Handle Data Heterogeneity for Domain Incremental Cardiac Segmentation
  Kang Li, Yu Zhu, Lequan Yu, Pheng-Ann Heng.
  IEEE Transactions on Medical Imaging (TMI), 2024.
  
• Boosting Multiple Instance Learning Models for Whole Slide Image Classification: A Model-agnostic Framework Based on Counterfactual Inference
  Weiping Lin, Zhenfeng Zhuang, Lequan Yu, Liansheng Wang.
  AAAI Conference on Artificial Intelligence (AAAI), 2024.
  

[code]

• Memory-Efficient Prompt Tuning for Incremental Histopathology Classification
  Yu Zhu, Kang Li, Lequan Yu, Pheng-Ann Heng.
  AAAI Conference on Artificial Intelligence (AAAI), 2024.
  

2023

• Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations
  Tsai Hor Chan, Kin Wai Lau, Jiajun Shen, Guosheng Yin, Lequan Yu.
  Conference on Neural Information Processing Systems (NeurIPS), 2023.
  

[code]

• IDRNet: Intervention-Driven Relation Network for Semantic Segmentation
  Zhenchao Jin, Xiaowei Hu, Lingting Zhu, Luchuan Song, Li Yuan, Lequan Yu.
  Conference on Neural Information Processing Systems (NeurIPS), 2023.
  

[code]

• ConSlide: Asynchronous Hierarchical Interaction Transformer with Breakup-Reorganize Rehearsal for Continual Whole Slide Image Analysis
  Yanyan Huang, Weiqin Zhao, Shujun Wang, Yu Fu, Yuming Jiang, Lequan Yu.
  International Conference on Computer Vision (ICCV), 2023.
  

[code]

• HIGT: Hierarchical Interaction Graph-Transformer for Whole Slide Image Analysis
  Ziyu Guo, Weiqin Zhao, Shujun Wang, Lequan Yu.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023.
  

[code]

• Make-A-Volume: Leveraging Latent Diffusion Models for Cross-Modality 3D Brain MRI Synthesis
  Lingting Zhu, Zeyue Xue, Zhenchao Jin, Xian Liu, Jingzhen He, Ziwei Liu, Lequan Yu.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023.
  
• Adaptive Region-Specific Loss for Improved Medical Image Segmentation
  Yizheng Chen, Lequan Yu, Jen-Yeu Wang, Neil Panjwani, Jean-Pierre Obeid, Wu Liu, Lianli Liu, Nataliya Kovalchuk, Michael Francis Gensheimer, Lucas Kas Vitzthum, Beth M Beadle, Daniel T Chang, Quynh-Thu Le, Bin Han, Lei Xing.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
  
• Shared-specific Feature Learning with Bottleneck Fusion Transformer for Multi-modal Whole Slide Image Analysis
  Zhihua Wang, Lequan Yu, Xin Ding, Xuehong Liao, Liansheng Wang.
  IEEE Transactions on Medical Imaging (TMI), 2023.
  
• RECIST-induced Reliable Learning: Geometry-driven Label Propagation for Universal Lesion Segmentation
  Lianyu Zhou, Lequan Yu, Liansheng Wang.
  IEEE Transactions on Medical Imaging (TMI), 2023.
  
• Transformer-based Multimodal Fusion for Survival Prediction by Integrating Whole Slide Images, Clinical, and Genomic Data
  Yihang Chen, Weiqin Zhao, Lequan Yu.
  IEEE International Symposium on Biomedical Imaging (ISBI), 2023.
  
• Histopathology Whole Slide Image Analysis with Heterogeneous Graph Representation Learning
  Tsai Hor Chan, Fernando Julio Cendra, Lan Ma, Guosheng Yin, Lequan Yu.
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
  

[code]

• Taming Diffusion Models for Audio-Driven Co-Speech Gesture Generation
  Lingting Zhu, Xian Liu, Xuanyu Liu, Rui Qian, Ziwei Liu, Lequan Yu.
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
  

[code]

• MagicNet: Semi-Supervised Multi-Organ Segmentation via Magic-Cube Partition and Recovery
  Duowen Chen, Yunhao Bai, Wei Shen, Qingli Li, Lequan Yu, Yan Wang.
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
  

[code]

• Hybrid Graph Convolutional Network with Online Masked Autoencoder for Robust Multimodal Cancer Survival Prediction
  Wentai Hou, Chengxuan Lin, Lequan Yu, Jing Qin, Rongshan Yu, Liansheng Wang.
  IEEE Transactions on Medical Imaging (TMI), 2023.
  
• MulGT: Multi-task Graph-Transformer with Task-aware Knowledge Injection and Domain Knowledge-driven Pooling for Whole Slide Image Analysis
  Weiqin Zhao, Shujun Wang, Maximus Yeung, Tianye Niu, Lequan Yu.
  AAAI Conference on Artificial Intelligence (AAAI), 2023.
  

[code]

2022

• Leveraging data-driven self-consistency for high-fidelity gene expression recovery
  Md Tauhidul Islam, Jen-Yeu Wang, Hongyi Ren, Xiaomeng Li, Masoud Badiei Khuzani, Shengtian Sang, Lequan Yu, Liyue Shen, Wei Zhao, Lei Xing.
  Nature Communications, 2022.
  
• Data Discernment for Affordable Training in Medical Image Segmentation
  Youyi Song, Lequan Yu, Baiying Lei, Kup-Sze Choi, Jing Qin.
  IEEE Transactions on Medical Imaging (TMI), 2022.
  

[code]

• MuRCL: Multi-instance Reinforcement Contrastive Learning for Whole Slide Image Classification
  Zhonghang Zhu, Lequan Yu, Wei Wu, Rongshan Yu, Defu Zhang, Liansheng Wang.
  IEEE Transactions on Medical Imaging (TMI), 2022.
  

[code]

• Multi-Granularity Cross-modal Alignment for Generalized Medical Visual Representation Learning
  Fuying Wang, Yuyin Zhou, Shujun Wang, Varut Vardhanabhuti, Lequan Yu.
  Conference on Neural Information Processing Systems (NeurIPS), 2022.
  

[code]

• MCIBI++: Soft Mining Contextual Information Beyond Image for Semantic Segmentation
  Zhenchao Jin, Dongdong Yu, Zehuan Yuan, Lequan Yu.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
  

[code]

• You Should Look at All Objects
  Zhenchao Jin, Dongdong Yu, Luchuan Song, Zehuan Yuan, Lequan Yu.
  European Conference on Computer Vision (ECCV), 2022.
  
• Domain-incremental Cardiac Image Segmentation with Style-oriented Replay and Domain-sensitive Feature Whitening
  Kang Li, Lequan Yu, Pheng-Ann Heng.
  IEEE Transactions on Medical Imaging (TMI), 2022.
  
• NestedFormer: Nested Modality-Aware Transformer for Brain Tumor Segmentation
  Zhaohu Xing, Lequan Yu, Liang Wan, Tong Han, Lei Zhu.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022.
  

[code]

• Joint Prediction of Meningioma Grade and Brain Invasion via Task-Aware Contrastive Learning
  Tianling Liu, Wennan Liu, Lequan Yu, Liang Wan, Tong Han, Lei Zhu.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022.
  
• Spatial-hierarchical Graph Neural Network with Dynamic Structure Learning for Histological Image Classification
  Wentai Hou, Helong Huang, Qiong Peng, Rongshan Yu, Lequan Yu, Liansheng Wang.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022.
  
• Reinforcement Learning Driven Intra-modal and Inter-modal Representation Learning for 3D Medical Image Classification
  Zhonghang Zhu, Liansheng Wang, Baptiste Magnier, Lei Zhu, Defu Zhang, Lequan Yu.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022.
  
• CD²-pFed: Cyclic Distillation-guided Channel Decoupling for Model Personalization in Federated Learning
  Yiqing Shen, Yuyin Zhou, Lequan Yu.
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
  
• H²-MIL: Exploring Hierarchical Representation with Heterogeneous Multiple Instance Learning for Whole Slide Image Analysis
  Wentai Hou, Lequan Yu, Chengxuan Lin, Helong Huang, Rongshan Yu, Jing Qin, Liansheng Wang.
  AAAI Conference on Artificial Intelligence (AAAI), 2022.
  
• Lymph Node Metastasis Prediction from Whole Slide Images with Transformer-guided Multi-instance Learning and Knowledge Transfer
  Zhihua Wang, Lequan Yu, Xin Ding, Xuehong Liao, Liansheng Wang.
  IEEE Transactions on Medical Imaging (TMI), 2022.
  
• Novel-view X-ray Projection Synthesis through Geometry-integrated Deep Learning
  Liyue Shen, Lequan Yu, Wei Zhao, John Pauly, Lei Xing.
  Medical Image Analysis (MedIA), 2022.
  
• Towards Reliable Cardiac Image Segmentation: Assessing Image-level and Pixel-level Segmentation Quality via Self-reflective References
  Kang Li, Lequan Yu, Pheng-Ann Heng.
  Medical Image Analysis (MedIA), 2022.
  
• Robust Medical Image Classification from Noisy Labeled Data with Global and Local Representation Guided Co-training
  Cheng Xue, Lequan Yu, Pengfei Chen, Qi Dou, Pheng-Ann Heng.
  IEEE Transactions on Medical Imaging (TMI), 2022.
  

2021

• Metal Artifact Reduction in 2D CT Images with Self-supervised Cross-domain Learning
  Lequan Yu, Zhicheng Zhang, Xiaomeng Li, Hongyi Ren, Wei Zhao, Lei Xing.
  Physics in Medicine & Biology (PMB), 2021.
  
• TransCT: Dual-path Transformer for Low Dose Computed Tomography
  Zhicheng Zhang, Lequan Yu, Xiaokun Liang, Wei Zhao, Lei Xing.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021.
  

  [code]

• Selective Learning from External Data for CT Image Segmentation
  Youyi Song, Lequan Yu, Baiying Lei, Kup-Sze Choi, Jing Qin.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021.
  Student Travel Award
  

  [code]

• Deep Neural Network with Consistency Regularization of Multi-Output Channels for Improved Tumor Detection and Delineation
  Hyunseok Seo, Lequan Yu, Hongyi Ren, Xiaomeng Li, Liyue Shen, Lei Xing.
  IEEE Transactions on Medical Imaging (TMI), 2021.
  
• Rotation-oriented Collaborative Self-supervised Learning for Retinal Disease Diagnosis
  Xiaomeng Li, Xiaowei Hu, Xiaojuan Qi, Lequan Yu, Wei Zhao, Pheng-Ann Heng, Lei Xing.
  IEEE Transactions on Medical Imaging (TMI), 2021.
  

  [code]

• MR to ultrasound image registration with segmentation-based learning for HDR prostate brachytherapy
  Yizheng Chen, Lei Xing, Lequan Yu, Wu Liu, Benjamin P Fahimian, Thomas Niedermayr, Hilary Bagshaw, Mark K Buyyounouski, Bin Han.
  Medical Physics, 2021.
  
• Modularized Data-Driven Reconstruction Framework for Non-ideal Focal Spot Effect Elimination in Computed Tomography
  Zhicheng Zhang, Lequan Yu, Wei Zhao, Lei Xing.
  Medical Physics, 2021.
  
• Deep Sinogram Completion with Image Prior for Metal Artifact Reduction in CT Images
  Lequan Yu, Zhicheng Zhang, Xiaomeng Li, Lei Xing.
  IEEE Transactions on Medical Imaging (TMI), 2021.
  

2020

• Dual-Teacher++: Exploiting Intra-domain and Inter-domain Knowledge with Reliable Transfer for Cardiac Segmentation
  Kang Li, Shujun Wang, Lequan Yu^†, Pheng-Ann Heng.
  IEEE Transactions on Medical Imaging (TMI), 2020.
  
• Automatic intraprostatic lesion segmentation in multiparametric magnetic resonance images with proposed multiple branch UNet
  Yizheng Chen, Lei Xing, Lequan Yu, Hilary P. Bagshaw, Mark K. Buyyounouski, Bin Han.
  Medical Physics, 2020.
  
• Learning from Extrinsic and Intrinsic Supervisions for Domain Generalization
  Shujun Wang, Lequan Yu^†, Caizi Li, Chi-Wing Fu, Pheng-Ann Heng.
  European Conference on Computer Vision (ECCV), 2020.
  

  [code]

• DoFE: Domain-oriented Feature Embedding for Generalizable Fundus Image Segmentation on Unseen Datasets
  Shujun Wang, Lequan Yu^†, Kang Li, Xin Yang, Chi-Wing Fu, Pheng-Ann Heng.
  IEEE Transactions on Medical Imaging (TMI), 2020.
  

  [code]

• Deep Mining External Imperfect Data for Chest X-ray Diseases Screening
  Luyang Luo*, Lequan Yu*, Hao Chen, Quande Liu, Xi Wang, Jiaqi Xu, Pheng-Ann Heng.
  IEEE Transactions on Medical Imaging (TMI), 2020.
  
• Semi-supervised Medical Image Classication with Relation-driven Self-ensembling Model
  Quande Liu, Lequan Yu^†, Luyang Luo, Qi Dou, Pheng-Ann Heng.
  IEEE Transactions on Medical Imaging (TMI), 2020.
  

  [code]

• Towards Cross-modality Medical Image Segmentation with Online Mutual Knowledge Distillation
  Kang Li, Lequan Yu^†, Shujun Wang, and Pheng-Ann Heng.
  AAAI Conference on Artificial Intelligence (AAAI), 2020.
  
• Robust Medical Image Segmentation from Non-expert Annotations with Tri-network
  Tianwei Zhang*, Lequan Yu*, Na Hu, Su Lv, Shi Gu.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020.
  
• Dual-Teacher: Integrating Intra-domain and Inter-domain Teachers for Annotation-efficient Cardiac Segmentation
  Kang Li, Shujun Wang, Lequan Yu^†, Pheng-Ann Heng.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020.
  
• Difficulty-aware Meta-learning for Rare Disease Diagnosis
  Xiaomeng Li, Lequan Yu, Yueming Jin, Chi-Wing Fu, Lei Xing, Pheng-Ann Heng.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020.
  
• Unsupervised Detection of Distinctive Regions on 3D Shapes
  Xianzhi Li, Lequan Yu, Chi-Wing Fu, Daniel Cohen-Or, Pheng-Ann Heng.
  ACM Transactions on Graphics (ACM TOG), 2020.
  

  [code]

• Transformation-consistent Self-ensembling Model for Semi-supervised Medical Image Segmentation
  Xiaomeng Li, Lequan Yu, Hao Chen, Chi-Wing Fu, Lei Xing, Pheng-Ann Heng.
  IEEE Transaction on Neural Network and Learning System (TNNLS), 2020.
  

  [code]

Before 2020

• Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation
  Lequan Yu, Shujun Wang, Xiaomeng Li, Chi-Wing Fu, and Pheng-Ann Heng.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019.
  

  [code]

• CANet: Cross-disease Attention Network for Joint Diabetic Retinopathy and Diabetic Macular Edema Grading
  Xiaomeng Li, Xiaowei Hu, Lequan Yu, Lei Zhu, Chi-Wing Fu, and Pheng-Ann Heng.
  IEEE Transactions on Medical Imaging (TMI), 2019.
  

  [code]

• RMDL: Recalibrated multi-instance deep learning for whole slide gastric image classification
  Shujun Wang, Yaxi Zhu, Lequan Yu, Hao Chen, Huangjing Lin, Xiangbo Wan, Xinjuan Fan, and Pheng-Ann Heng.
  Medical Image Analysis (MedIA), 2019.
  
• Patch-based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentation
  Shujun Wang, Lequan Yu, Xin Yang, Chi-Wing Fu, and Pheng-Ann Heng.
  IEEE Transactions on Medical Imaging (TMI), 2019.
  Ranked 1st place in REFUGE 2018 Optic Disc and Cup Segmentation Challenge
  

  [project]

• PU-Net: Point Cloud Upsampling Network
  Lequan Yu, Xianzhi Li, Chi-Wing Fu, Daniel Cohen-Or, Pheng-Ann Heng.
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
  

  [project] [code] [supp] [poster]

• EC-Net: an Edge-aware Point set Consolidation Network
  Lequan Yu, Xianzhi Li, Chi-Wing Fu, Daniel Cohen-Or, Pheng-Ann Heng.
  European Conference on Computer Vision (ECCV), 2018.
  

  [project] [code] [supp]

• Towards Automated Semantic Segmentation in Prenatal Volumetric Ultrasound
  Xin Yang, Lequan Yu, Shengli Li, Huaxuan Wen, Dandan Luo, Cheng Bian, Jing Qin, Dong Ni, Pheng-Ann Heng.
  IEEE Transactions on Medical Imaging (TMI), 2018.
  

  [project]

• Volumetric ConvNets with Mixed Residual Connections for Automated Prostate Segmentation from 3D MR Images
  Lequan Yu, Xin Yang, Hao Chen, Jing Qin, Pheng-Ann Heng.
  AAAI Conference on Artificial Intelligence (AAAI), 2017. [Oral Presentation]
  Ranked 1st on Prostate MR Image Segmentation (PROMISE12) leaderboard, until Jan. 2018.
  

  [challenge website]

• Automatic 3D Cardiovascular MR Segmentation with Densely-Connected Volumetric ConvNets
  Lequan Yu, Jie-Zhi Cheng, Qi Dou, Xin Yang, Hao Chen, Jing Qin, Pheng-Ann Heng.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2017.
  

  [project] [code]

• Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks
  Lequan Yu, Hao Chen, Qi Dou, Jing Qin, Pheng-Ann Heng.
  IEEE Transactions on Medical Imaging (TMI), 2017.
  ESI Highly Cited Paper
  Ranked 1st place in Skin Lesion Analysis Towards Melanoma Detection Challenge (ISIC 2016)
  

  [project] [code] [challenge website]

• Integrating Online and Offline 3D Deep Learning for Automated Polyp Detection in Colonoscopy Videos
  Lequan Yu, Hao Chen, Qi Dou, Jing Qin, Pheng-Ann Heng.
  IEEE Journal of Biomedical and Health Informatics (JBHI), 2017.
  
• 3D Deeply Supervised Network for Automated Segmentation of Volumetric Medical Images
  Qi Dou, Lequan Yu, Hao Chen, Yueming Jin, Xin Yang, Jing Qin, Pheng-Ann Heng.
  Medical Image Analysis (MedIA), 2017.
  ESI Highly Cited Paper
  MedIA-MICCAI'17 Best Paper Award
  

  [code]

• 3D FractalNet: Dense Volumetric Segmentation for Cardiovascular MRI Volumes
  Lequan Yu, Xin Yang, Jing Qin, Pheng-Ann Heng.
  MICCAI Workshop on Whole-Heart and Great Vessel Segmentation from 3D Cardiovascular MRI in Congenital Heart Disease, 2016.
  Ranked 1st place in Whole-Heart and Great Vessel Segmentation Challenge
  

  [challenge website]

• Automatic Detection of Cerebral Microbleeds from MR Images via 3D Convolutional Neural Networks
  Qi Dou*, Hao Chen*, Lequan Yu, Lei Zhao, Jing Qin, Defeng Wang, Vincent CT Mok, Lin Shi, Pheng-Ann Heng.
  IEEE Transactions on Medical Imaging (TMI), 2016.
  ESI Highly Cited Paper
  

  [project]

Students

Recent Talks & Presentations

• Leveraging Deep Learning in Computational Pathology: from Single-modal to Multi-modal Analysis
  at The Third Affiliated Hospital of Sun Yat-sen University, April 2024.
  at Zhejiang Lab, Hangzhou, July 2023.
  at Shanghai AI Lab, Shanghai, July 2023.
  at Computational Health seminar, Helmholtz AI, German, July 2023.
  
• Learning generalized medical visual representation from accompanied medical reports
  at MICS online seminar, April 2023.
  at Department of Biomedical Engineering, SZU, April 2023.
  
• Medical Image Analysis and Reconstruction with Data-efficient Learning
  at VALSE 2022 workshop "医学数据分析中的深度学习方法", August 2022.
  at Beihang University, May 2022.
  at Zhejiang University, May 2022.
  at 海峡两岸暨港澳精准医学青年博士论坛, November 2021.
  at 中国医师协会第十五次放射医师年会, October 2021.
  at Nanjing University of Information Science and Technology, October 2021.
  at Department of Electrical and Electronic Engineering, HKU, September 2021.
  at MICS 2021, July 2021.
  at Data Science and Computational Statistics Seminar, University of Birmingham, February 2021.
  
• AI for Medical Imaging: Applications and Beyond
  at AI and Big Data Research for Health Improvement Symposium, Institute of Data Science, HKU, August 2022.
  at Mini-Symposium on Interdisciplinary Research, Faculty of Science, HKU, January 2022.
  at School of Biomedical Sciences, HKU, December 2021.
  
• The Applications of Transformer in Volumetric Segmentation and Low Dose CT
  at VALSE Webinar, October 2022.
  

Honors & Awards

Professional Activities

Teaching