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Short Bio

I am now a post-doc at the Department of Computing, Imperial College London, supervised by Dr. Ben Glocker in BioMedIA. Before that, I obtained my Ph.D. degree in the Department of Computer Science and Engineering, The Chinese University of Hong Kong (CUHK), supervised by Prof. Pheng Ann Heng in July 2018. I received B. Eng. degree in Biomedical Engineering from Beihang University (BUAA) in Beijing, June 2014. I worked with Dr. Yan Xu for undergraduate research in MSRA.


Research Interests

Medical Image Analysis, Deep Learning, Machine Learning.

I focus on interdisciplinary researches at medical image analysis and artificial intelligence, for improving lesion detection, anatomical structure segmentation and quantification, cancer diagnosis and therapy, and surgical robotic perception. I have expertise in 3D deep learning for high-dimensional medical image computing.

Recently, I widely investigate model generalization and robustness related topics in machine learning for medical scenarios.


News

  • [07/2019] Session Chair at MIDL'19.
  • [06/2019] Keynote Speaker at OR 2.0 Context-Aware Operating Theaters Workshop, MICCAI'19.
  • [06/2019] Five papers accepted to MICCAI'19.
  • [02/2019] Three papers accepted to IPMI'19, TMI and Radiology.
  • [12/2018] Two papers accepted to MedIA and ISBI'19.
  • [12/2018] I honourably received the HK Institution of Science 2018 Young Scientist Award in Engineering Science.
  • [10/2018] Two papers accepted to International Journal of Human-Computer Studies and AAAI'19 (oral).
  • [09/2018] Two papers appeared in MICCAI-MLMI'18 (oral) and MICCAI-DLMIA'18.
  • [07/2018] I honourably received the Postgraduate Research Output Award of Faculty of Engineering at CUHK.
  • [04/2018] Paper on cross-modality domain adaptation in medical images has been accepted to IJCAI'18.
  • [01/2018] Four papers accepted to TMI, JAMA, AAAI'18 and ISBI'18.

Selected Publications

For a complete list, please check my google scholar.

Improving RetinaNet for CT Lesion Detection with Dense Masks from Weak RECIST Labels.
Martin Zlocha, Qi Dou, Ben Glocker. [paper] [live demo]
Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019. (To appear)

Incorporating Temporal Prior from Motion Flow for Instrument Segmentation in Minimally Invasive Surgery Video.
Yueming Jin, Keyun Cheng, Qi Dou, Pheng Ann Heng. [paper] [code]
Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019. (Oral) (To appear)

Robust Learning at Noisy Labeled Medical Images: Applied to Skin Lesion Classification.
Cheng Xue, Qi Dou, Xueying Shi, Hao Chen, and Pheng Ann Heng. [paper]
IEEE International Symposium on Biomedical Imaging (ISBI), 2019.

Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation.
Cheng Chen, Qi Dou, Hao Chen, Jing Qin, and Pheng Ann Heng. [paper] [code]
Association for the Advancement of Artificial Intelligence (AAAI), 2019. (Oral)

PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network at Unpaired Cross-modality Cardiac Segmentation.
Qi Dou*, Cheng Ouyang*, Cheng Chen, Hao Chen, Ben Glocker, Xiahai Zhuang, and Pheng Ann Heng. [paper] [code]
IEEE Access, 2019 (extended version of unsupervised feature-level domain adaptation in CT/MRI)

Unsupervised Cross-Modality Domain Adaptation of ConvNets for Biomedical Image Segmentations
with Adversarial Loss.

Qi Dou*, Cheng Ouyang*, Cheng Chen, Hao Chen, and Pheng Ann Heng. [paper] [code]
International Joint Conference on Artificial Intelligence (IJCAI), 2018. (Oral)

Semantic-Aware Generative Adversarial Nets for Unsupervised Domain Adaptation in Chest X-ray Segmentation.
Cheng Chen, Qi Dou, Hao Chen, and Pheng Ann Heng. [paper]
Machine Learning in Medical Imaging (MLMI) Workshop of MICCAI, 2018. (Oral)

SV-RCNet: Workflow Recognition from Surgical Videos Using Recurrent Convolutional Network.
Yueming Jin*, Qi Dou*, Hao Chen, Lequan Yu, Jing Qin, Chi-Wing Fu, and Pheng Ann Heng. [paper] [code]
IEEE Transactions on Medical Imaging (TMI), 2018.

3D Multi-scale FCN with Random Modality Voxel Dropout Learning for Intervertebral Disc Localization and Segmentation from Multi-modality MR Images.
Xiaomeng Li, Qi Dou, Hao Chen, Chi-Wing Fu, Xiaojuan Qi, Guoyan Zheng, Pheng Ann Heng, et al. [paper]
Medical Image Analysis (MedIA), 2018

SFCN-OPI: Detection and Fine-grained Classification of Nuclei Using Sibling FCN with Objectness Prior Interaction.
Yanning Zhou, Qi Dou, Hao Chen, Jing Qin, and Pheng Ann Heng. [paper]
Association for the Advancement of Artificial Intelligence (AAAI), 2018. (Spotlight)

Automated Pulmonary Nodule Detection via 3D ConvNets with Online Sample Filtering and
Hybrid-Loss Residual Learning.

Qi Dou, Hao Chen, Yueming Jin, Huangjing Lin, Jing Qin, and Pheng Ann Heng. [paper]
Medical Image Computing and Computer Assisted Intervention (MICCAI), 2017.

3D Deeply Supervised Network for Automated Segmentation of Volumetric Medical Images.
Qi Dou, Lequan Yu, Hao Chen, Yueming Jin, Xin Yang, Jing Qin, and Pheng Ann Heng. [paper]
Medical Image Analysis (MedIA), 2017.
(MedIA-MICCAI'17 Best Paper Award)

VoxResNet: Deep Voxelwise Residual Networks for Brain Segmentation from 3D MR Images.
Hao Chen, Qi Dou, Lequan Yu, Jing Qin, and Pheng Ann Heng. [paper]
NeuroImage, 2017.

Multi-level Contextual 3D CNNs for False Positive Reduction in Pulmonary Nodule Detection.
Qi Dou, Hao Chen, Lequan Yu, Jing Qin, and Pheng Ann Heng. [paper]
IEEE Transactions on Biomedical Engineering (TBME), 2017.
Listed among the Most Popular Articles Published in 2017

3D Fully Convolutional Networks for Intervertebral Disc Localization and Segmentation.
Hao Chen*, Qi Dou*, Xi Wang, Jing Qin, Jack C. Y. Cheng and Pheng Ann Heng. [paper]
International Conference on Medical Imaging and Augmented Reality (MIAR), 2016.
(Best Paper Award)

3D Deeply Supervised Network for Automatic Liver Segmentation from CT Volumes.
Qi Dou, Hao Chen, Yueming Jin, Lequan Yu, Jing Qin, and Pheng Ann Heng. [paper]
Medical Image Computing and Computer Assisted Intervention (MICCAI), 2016.
(Young scientist award finalist, Student travel award)

Automatic Detection of Cerebral Microbleeds from MR Images via 3D Convolutional Neural Networks.
Qi Dou*, Hao Chen*, Lequan Yu, Jing Qin, Lin Shi, Pheng Ann Heng, et al. [paper] [code & data]
IEEE Transactions on Medical Imaging (TMI), 2016.

Mitosis Detection in Breast Cancer Histology Images via Deep Cascaded Networks.
Hao Chen, Qi Dou, Xi Wang, Jing Qin and Pheng Ann Heng. [project]
The Association for the Advancement of Artificial Intelligence (AAAI), 2016. (Oral)

Automatic Fetal Ultrasound Standard Plane Detection Using Knowledge Transferred Recurrent Neural Networks.
Hao Chen, Qi Dou, Dong Ni, Jie-Zhi Cheng, Jing Qin, Shengli Li and Pheng Ann Heng. [porject]
Medical Image Computing and Computer Assisted Intervention (MICCAI), 2015.

Automatic Cerebral Microbleeds Detection from MR Images via Independent Subspace Analysis Based Hierarchical Features.
Qi Dou, Hao Chen, Lequan Yu, Lin Shi, Defeng Wang, Vincent CT Mok and Pheng Ann Heng. [paper]
Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015. (Oral)

(* indicates equal contribution)


Selected Awards

  • CUHK Faculty Outstanding Thesis Award 2018
  • Hong Kong Institution of Science 2018 Young Scientist Award in Engineering Science (one winner per year in HK)
  • Postgraduate Research Output Award 2017 at CUHK (one winner per year in Faculty of Engineering at CUHK)
  • Best Paper Award of Medical Image Analysis-MICCAI 2017 (first-author)
  • Young Scientist Award Runner Up, MICCAI 2016 (first-author)
  • Student Travel Award, MICCAI 2016
  • Best Paper Award of International Doctoral Forum 2016 (first-author)
  • Best Paper Award of International Conference on Medical Imaging and Augmented Reality 2016 (co-first-author)
  • Winner of Challenge on Lung Nodule False Positive Reduction, ISBI 2016 (first-author)
  • Winner of Challenge on Surgical Video Analysis, MICCAI 2016 (co-first-author)
  • Winner of Challenge on Automatic IVD Localization and Segmentation in MR Images, MICCAI 2015&2016 (co-author)
  • Honoured Graduate Award at Beihang University, 2014


Talks

Talk on "Endoscopy Surgical Video Analysis with Machine Learning"
at MICCAI'19 Workshop of OR 2.0 Context-Aware Operating Theaters, Oct 2019. (coming soon)

Talk on "Multimodal Learning from Unpaired Medical Images for Adaptation and Integration"
at UCL Medical Image Computing Summer School (MedICSS), UK, July 2019.
at UCL/ICL Bio-Imaging Symposium, UK, May 2019.

Talk on "Analyzing High Dimensional Medical Images with Deep Learning"
at Hamlyn Centre for Robotic Surgery, Imperial College London, UK, Feb 2019.
at Smart Robotics and Artificial Intelligence Workshop organized by Signate Life Sciences, HK, Dec 2018.

Talk on "Towards AI-Powered Healthcare: Automated Medical Image Computing via Deep Learning"
at Department of Computer Science, Sheffield University, May 2019.
at Department of Computer Science & Engineering, CUHK, Mar 2019.
at Department of Computer Science & Engineering, HKUST, Feb 2019.
at Hong Kong Instuition of Science Annual Meeting, HK, Dec 2018.

Talk on "Deep Learning for AI-Powered Medical Image Analysis in Radiology"
at Hong Kong College of Radiologists (HKCR) Annual Scientific Meeting, HK, November 2018.

Talk at Engineering Medical Innovation (EMedI) Summit 2018.
organized by CUHK Chow Yuk Ho Technology Center for Innovative Medicine, August 2018.

Talk on "Deep Learning for Medical Image Computing"
at Department of Computing, HKPolyU, HK, August 2018.

Talk on "Medical Image Computing via Deep Learning -- Detection and Segmentation"
at BioMedIA lab in Imperial College London, UK, July 2018.
at German Center for Neurodegenerative Diseases (DZNE), Germany, July 2018.

Talk on "Intelligent Medical Image Detection and Segmentaiton via 3D Deep Learning"
at AI in Healthcare Summit organized by ReWork, HK, June 2018. [link]

Talk on "Deep Learning for Medical Image Analysis: Algorithms and Applications"
at Department of Clinical Oncology at Queen Mary Hospital HKU, HK, April 2018.

Talk on "3D Convolutional Networks for Computer-aided Lesion Detection in Medical Images"
at A*Star Institute of High Performance Computing, Singapore, May 2017.

Talk on "Automated Brain Lesion Detection in MRI Scans with Hierarchical Features"
at Siemens Corporate Research, Princeton, US, June 2016.


Press Coverage

  • China Daily, AI used to pinpoint head and neck cancer treatment, Apr 2019. [link]
  • CUHK CSE News of Achievement, 2018. [link]
  • CUHK Engineering Social Media Platform, keywords #healthcaretechnology, #womanengineering, 2018. [link]
  • CUHK Updates, An Eagle Eye for Smart Diagnoses, 2018. [link]
  • CUHK Faculty of Engineering Press, Engineering Today for Tomorrow, 2017. [link]
  • Regional press media, AI for Lung Cancer and Brease Cancer Analysis, 2017. [link]


Professional Activities

Conference Services:

Area Chair of MIDL'19
PC of AAAI'19-20, IJCAI'18-19, "Medical Imaging meets NeurIPS" 18-19
Reviewer of MICCAI'17-19, IROS'19

Journal Reviews:

IEEE Transactions on Pattern Analysis and Machine Learning
Medical Image Analysis
IEEE Transactions on Medical Imaging
International Journal of Computer Vision
IEEE Transactions on Biomedical Engineering
IEEE Transactions on Neural Networks and Learning Systems
IEEE Transactions on Automation Science and Engineering
IEEE Transactions on Cybernetics
IEEE Journal of Biomedical and Health Informatics
IEEE Transactions on Emerging Topics in Computing
International Journal of Computer Assisted Radiology and Surgery
The Lancet Digital Health
NeuroImage
Neurocomputing
Pattern Recognition
Medical Physics
BMC Bioinformatics
Computerized Medical Imaging and Graphics
Neuroradiology
Journal of Magnetic Resonance Imaging
International Journal of Imaging Systems and Technology
SPIE Journal of Medical Imaging
SPIE Journal of Electronic Imaging
Informatics in Medicine Unlocked
etc.

Membership of IEEE, IEEE EMBS, MICCAI Society.


Miscellany

I like cycling, yoga, cooking, reading, travelling.

Understanding others is intelligent, understanding yourself is wisdom.


Last updated date: July 2019.

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