World's Best Scientists 2026 revealed!
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Rising Stars
2025

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Rising Stars

D-Index
65
Citations
22573
World Ranking
115
National Ranking
39

Computer Science

D-Index
72
Citations
28015
World Ranking
1644
National Ranking
221

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Qi Dou is affiliated with the Chinese University of Hong Kong in China. Their research spans several interconnected fields including Computer Science, Medicine, and Engineering, with a focus on specific subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, and Surgery.

The scientist has contributed to a range of main topics in medical imaging and related areas. These include Surgical Simulation and Training, Radiomics and Machine Learning in Medical Imaging, Advanced Neural Network Applications, AI in cancer detection, Domain Adaptation and Few-Shot Learning, Advanced Vision and Imaging, and Medical Image Segmentation Techniques.

Qi Dou's publication record features papers in respected venues with notable examples including:

  • 'The Liver Tumor Segmentation Benchmark (LiTS)', 2022, Medical Image Analysis
  • 'Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentation', 2020, IEEE Transactions on Medical Imaging
  • 'Federated learning enables big data for rare cancer boundary detection', 2022, Nature Communications
  • 'Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study', 2021, npj Digital Medicine
  • 'Contrastive Cross-Site Learning With Redesigned Net for COVID-19 CT Classification', 2020, IEEE Journal of Biomedical and Health Informatics

Their frequent coauthors comprise Pheng-Ann Heng, Yunhui Liu, Yonghao Long, Yueming Jin, and Meirui Jiang.

Qi Dou has published extensively with Springer Science+Business Media, contributing to 10 book publications. These works include titles such as Medical Image Computing and Computer Assisted Intervention - MICCAI 2022 and Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health, spanning years 2021 and 2022. Several of these books have received citations, highlighting the academic presence of these contributions.

The scientist regularly publishes in prominent venues including arXiv (Cornell University), IEEE Transactions on Medical Imaging, Medical Image Analysis, IEEE Robotics and Automation Letters, and Advanced Intelligent Systems. The concentration of work in these outlets reflects the interdisciplinary nature of their research, combining advanced computational methods with medical applications.

Best Publications

  • Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer.

    Babak Ehteshami Bejnordi;Mitko Veta;Paul Johannes van Diest;Bram van Ginneken

  • H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation From CT Volumes

    Xiaomeng Li;Hao Chen;Xiaojuan Qi;Qi Dou

  • Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge.

    Arnaud Arindra Adiyoso Setio;Alberto Traverso;Thomas de Bel;Moira S.N. Berens

  • Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks

    Lequan Yu;Hao Chen;Qi Dou;Jing Qin

  • The Liver Tumor Segmentation Benchmark (LiTS)

    Patrick Bilic;Patrick Ferdinand Christ;Eugene Vorontsov;Grzegorz Chlebus

  • VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images

    Hao Chen;Qi Dou;Lequan Yu;Jing Qin

  • Automatic Detection of Cerebral Microbleeds From MR Images via 3D Convolutional Neural Networks

    Qi Dou;Hao Chen;Lequan Yu;Lei Zhao

  • 3D deeply supervised network for automated segmentation of volumetric medical images.

    Qi Dou;Lequan Yu;Hao Chen;Yueming Jin

  • Multilevel Contextual 3-D CNNs for False Positive Reduction in Pulmonary Nodule Detection

    Qi Dou;Hao Chen;Lequan Yu;Jing Qin

  • DCAN: Deep contour-aware networks for object instance segmentation from histology images

    Hao Chen;Xiaojuan Qi;Lequan Yu;Qi Dou

  • FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space

    Quande Liu;Cheng Chen;Jing Qin;Qi Dou

  • Domain Generalization via Model-Agnostic Learning of Semantic Features

    Qi Dou;Daniel Coelho de Castro;Konstantinos Kamnitsas;Ben Glocker

  • Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentation

    Cheng Chen;Qi Dou;Hao Chen;Jing Qin

  • Federated learning enables big data for rare cancer boundary detection

    Unknown

  • Weakly Supervised Deep Learning for Whole Slide Lung Cancer Image Analysis

    Xi Wang;Hao Chen;Caixia Gan;Huangjing Lin

  • 3D Deeply Supervised Network for Automatic Liver Segmentation from CT Volumes

    Qi Dou;Hao Chen;Yueming Jin;Lequan Yu

  • FedBN: Federated Learning on Non-IID Features via Local Batch Normalization

    Xiaoxiao Li;Meirui Jiang;Xiaofei Zhang;Michael Kamp

  • Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation

    Cheng Chen;Qi Dou;Hao Chen;Jing Qin

  • Harmonizing Transferability and Discriminability for Adapting Object Detectors

    Chaoqi Chen;Zebiao Zheng;Xinghao Ding;Yue Huang

  • MILD-Net: Minimal information loss dilated network for gland instance segmentation in colon histology images.

    Simon Graham;Hao Chen;Jevgenij Gamper;Qi Dou

  • Deep Learning for Automated Contouring of Primary Tumor Volumes by MRI for Nasopharyngeal Carcinoma

    Li Lin;Qi Dou;Yue Ming Jin;Guan Qun Zhou

  • Unsupervised cross-modality domain adaptation of convnets for biomedical image segmentations with adversarial loss

    Qi Dou;Cheng Ouyang;Cheng Chen;Hao Chen

Frequent Co-Authors

Pheng-Ann Heng
Pheng-Ann Heng Chinese University of Hong Kong
Hao Chen
Hao Chen Chinese University of Hong Kong
Jing Qin
Jing Qin Hong Kong Polytechnic University
Lequan Yu
Lequan Yu University of Hong Kong
Ben Glocker
Ben Glocker Imperial College London
Chi-Wing Fu
Chi-Wing Fu Chinese University of Hong Kong
Yun-Hui Liu
Yun-Hui Liu Chinese University of Hong Kong
Xiaojuan Qi
Xiaojuan Qi University of Hong Kong
Yun-Hui Liu
Yun-Hui Liu Chinese University of Hong Kong
Konstantinos Kamnitsas
Konstantinos Kamnitsas University of Oxford

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