Lequan Yu Assistant Professor Run Run Shaw Building, Rm 226 Department of Statistics and Actuarial Science The University of Hong Kong Hong Kong Email: lqyu [at] hku [dot] hk

Biography

I am currently an assistant professor at The University of Hong Kong. My research lies at the intersection of artificial intelligence and medical image analysis. I am dedicated to designing data-efficient learning methods for biomedical image analysis and reconstruction. I also have expertise in deep learning for 3D vision.

Before joining HKU, I was a postdoctoral research fellow in Stanford University, working with Prof. Lei Xing. I obtained my Ph.D. degree in CSE, The Chinese University of Hong Kong, supervised by Prof. Pheng-Ann Heng and Prof. Chi-Wing Fu in July 2019. Before that, I received the B.Eng degree in CS, Zhejiang University in 2015, under the supervision of Prof. Deng Cai.

I am looking for self-motivated PhD students, postdocs, research assistants, and (remote) summer interns, who are interested in artificial intelligence for healthcare. Welcome to drop me an email with your CV and transcripts. Remote collaboration is also welcome!

If you are an HKU student interested in doing research with me, please send me an email.

News

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]

* indicates equal contribution; ^† indicates corresponding authorship.

2021

• 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.
  
• 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]

2019

• 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.
  
• Boundary and Entropy-driven Adversarial Learning for Fundus Image Segmentation
  Shujun Wang*, Lequan Yu*, Kang Li, Xin Yang, Chi-Wing Fu, and Pheng-Ann Heng.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019.
  

  [code]

• 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]

2018

• 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]

• 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]

• 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]

• Semi-supervised Skin Lesion Segmentation via Transformation Consistent Self-ensembling Model
  Xiaomeng Li, Lequan Yu, Hao Chen, Chi-Wing Fu, Pheng-Ann Heng.
  British Machine Vision Conference (BMVC), 2018.
  

Before 2018

• 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]

• 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]

• 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.
  
• Towards Automatic Semantic Segmentation in Volumetric Ultrasound
  Xin Yang, Lequan Yu, Shengli Li, Xu Wang, Na Wang, Jing Qin, Dong Ni, Pheng-Ann Heng.
  Medical Image Computing and Computer Assisted Intervention (MICCAI), 2017. [Oral Presentation]
  

  [project]

• Fine-grained Recurrent Neural Networks for Automatic Prostate Segmentation in Ultrasound Images
  Xin Yang, Lequan Yu, Lingyun Wu, Yi Wang, Dong Ni, Jing Qin, Pheng-Ann Heng.
  AAAI Conference on Artificial Intelligence (AAAI), 2017. [Oral Presentation]
  
• 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

Previous Mentorship:

Kang Li (Ph.D. at CUHK)

Shujun Wang (Ph.D. at CUHK) (incoming Postdoc at Stanford)

Liyue Shen (Ph.D. at Stanford)

Xianzhi Li (Ph.D. at CUHK) (now, Postdoc at CUHK)

Honors & Awards

CUHK Young Scholars Thesis Award 2019

Young Scientist Award Short-listed, Hong Kong Institution of Science, 2019

Teaching Assistant of Merit, 2018

MedIA-MICCAI'17 Best Paper Award, 2017

AAAI Scholarship, San Fransisco, USA, 2017

Champion, Optic Disc&Cup Segmentation on Retinal Fundus Images (REFUGE 2018)

Champion, Whole-Heart and Great Vessel Segmentation (HVSMR 2016)

Champion, Skin Lesion Analysis Towards Melanoma Detection Challenge (ISIC 2016)

Champion, Prostate MR Image Segmentation 2012 (PROMISE12, until 2018 Jan.)

National Scholarship in China (1.8%), 2012-2014

He Zhijun Scholarship (1/300+, Highest Honor in College of Computer Science, Zhejiang University), 2014

Kwanjeong Educational Foundation Scholarship, 2012-2014

Meritorious Winner, Interdisciplinary Contest in Modeling (ICM), Consortium for Mathematics and Its Application, 2014

The Outstanding Undergraduate Award (Awarded by CCF, 100 undergraduates every year in China), 2014

Outstanding Graduates of Zhejiang University, 2015

Professional Activities

Conference Reviews:
Senior PC of International Joint Conference on Artificial Intelligence (IJCAI’21)
PC of AAAI Conference on Artificial Intelligence (AAAI’20-21)
IEEE International Conference on Computer Vision (ICCV’21, ICCV'19)
IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19-21)
Medical Image Computing and Computer Assisted Intervention (MICCAI’18-21)
IEEE Winter Conference on Applications of Computer Vision (WACV’20-21)
Medical Imaging with Deep Learning (MIDL’21)
SIGGRAPH 2020
European Conference on Computer Vision (ECCV’20)
Asian Conference on Computer Vision (ACCV’20)

Journal Reviews:
Nature Machine Intelligence
Medical Image Analysis (MedIA)
IEEE Transactions on Medical Imaging (TMI)
IEEE Transactions on Image Processing (TIP)
IEEE Transactions on Biomedical Engineering (TBME)
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
IEEE Transactions on Automation Science and Engineering (TASE)
IEEE Transactions on Artificial Intelligence (TAI)
IEEE Transactions on Big Data (TBD)
IEEE Transactions on Dependable and Secure Computing
IEEE Journal of Biomedical and Health Informatics (JBHI)
IEEE Robotics and Automation Letters (RA-L)
ACM Transactions on Computing for Healthcare
Medical Physics
Neurocomputing
International Journal of Computer Assisted Radiology and Surgery (IJCARS)
International Journal of Medical Informatics
Journal of Applied Clinical Medical Physics (JACMP)
Artificial Intelligence in Medicine
Computer Methods and Programs in Biomedicine (CMPB)

Teaching

2015-2016	Fall	CSCI1130 Introduction to Computing Using Java
2015-2016	Spring	CSCI3180 Principles of Programming Languages
2016-2017	Fall	ENGG5108 Big Data Analytics
2016-2017	Spring	CSCI3150 Introduction to Operating Systems
2017-2018	Fall	CSCI3150 Introduction to Operating Systems
2017-2018	Spring	CSCI3150 Introduction to Operating Systems