Cheng Ouyang, Ph.D.

About Me

Hi there!

I am a lecturer at the Department of Engineering Science, University of Oxford. Previously, I was a postdoctoral researcher at the Institute of Clinical Sciences, Imperial College London. Before that, I obtained my PhD at the Department of Computing, Imperial College London in April 2023.

Research Interests

• Multimodal machine learning for healthcare data (e.g., image, signal, and language)
• Domain generalization and uncertainty modeling for trustworthy machine learning in medical image computing
• Few-/zero-shot learning for data-efficient machine learning in medical image computing

• Machine learning for medical sciences

  Key words: Uncertainty Estimation; Domain generalization; Few-shot/Zero-shot Learning; Semantic Image Segmentation; MRI Reconstruction; Cardiac Imaging

News

• [Apr. 2024] Started my lectureship at Department of Engineering Science, University of Oxford.
• [Apr. 2024] We are calling for participants for the CMRxRecon2024 Challenge and UNSURE 2024 Workshop at MICCAI 2024.
• [Dec. 2023] Awarded the Imperial College London Seeds for Success Fund, for the topic of trustworthy machine learning for MRI reconstruction (project lead, 2024 cohort).
• [Nov. 2023] Our paper about test-time adaptation for MRI super-resolution was accepted for Med-NeurIPS 2023.
• [Oct. 2023] Awarded as a gold distinguished reviewer for IEEE Transactions on Medical Imaging.
• [Aug. 2023] An invitated talk Generalizable and data-efficient medical image computing is given to the School of Computer Science, University of Birmingham.
• [Aug. 2023] Awarded the Dame Julia Higgins Postdoc Collaborative Research Fund.
• [June. 2023] Our paper about topology-aware medical image segmentation was accepted for MICCAI 2023.
• [Sep. 2022] We won the Fetal Tissue Annotation and Segmentation Challenge (FeTA), MICCAI 2022.
• [Aug. 2022] Our paper about single-source domain generalization was accepted for IEEE Transactions on Medical Images (IEEE-TMI).
• [Jul. 2022] Our paper about probability calibration for medical image segmentation was accepted for MICCAI-UNSURE 2022 for a long oral presentation.
• [Jun. 2022] Our paper about robust medical image segmentation was accepted for MICCAI 2022.
• [May 2022] An invitated talk Generalizing deep-learning-based medical image segmentation across domains and classes is given to the Imaging Biomarkers and Computer-Aided Diagnosis Laboratory at NIH Clinical Center.
• [Feb. 2022] Our extension paper about self-supervised few-shot medical image segmentation was accepted for IEEE Transactions on Medical Images (IEEE-TMI).
• [Aug. 2021] Awarded as an outstanding reviewer for ICCV 2021.
• [Jun. 2021] Our paper about robust cardiac magnetic resonance image segmentation was accepted for MICCAI 2021.
• [Aug. 2020] Our paper about self-supervised few-shot medical image segmentation was accepted for ECCV 2020.

Selected Publications

• Improved Post-hoc Probability Calibration for Out-of-domain MRI Segmentation
  Cheng Ouyang, Shuo Wang, Chen Chen, Zeju Li, Wenjia Bai, Bernhard Kainz, Daniel Rueckert
  MICCAI-UNSURE 2022.
  [Paper]

• Causality-inspired Single-source Domain Generalization for Medical Image Segmentation
  Cheng Ouyang, Chen Chen, Surui Li, Zeju Li, Chen Qin, Wenjia Bai, Daniel Rueckert
  IEEE-TMI 2022.
  [Paper] [Code]

• Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation
  Cheng Ouyang, Carlo Biffi, Chen Chen, Turkay Kart, Huaqi Qiu, Daniel Rueckert
  ECCV 2020 & IEEE-TMI 2022.
  [Paper] [Code]

• Data Efficient Unsupervised Domain Adaptation for Cross-Modality Image Segmentation
  Cheng Ouyang, Konstantinos Kamnitsas, Carlo Biffi, Jinming Duan, Daniel Rueckert
  MICCAI 2019.
  [Paper]

• Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation
  Chen Chen*, Cheng Ouyang*, Giacomo Tarroni, Jo Schlemper, Huaqi Qiu, Wenjia Bai, Daniel Rueckert (*equal controbution)
  Winner solution to the Multi-sequence Cardiac MR Segmentation Challenge in MICCAI-STACOM’19 workshop.
  [Paper]

Academic Services

• Co-organizer:

  Cardiac MRI Reconstruction Challenge (CMRxRecon) at MICCAI 2024 link

  Uncertainty for Safe Utilization of Machine Learning in Medical Imaging Workshop at MICCAI 2024 link

  Extreme Cardiac MRI Analysis Challenge under Respiratory Motion (CMRxMotion) at MICCAI 2022 link

• Reviewer:

  International Conference on Machine Learning (ICML)

  International Conference on Learning Representations (ICLR)

  Conference on Neural Information Processing Systems (NeurIPS)

  The Conference on Computer Vision and Pattern Recognition (CVPR)

  International Conference on Computer Vision (ICCV)

  The European Conference on Computer Vision (ECCV)

  Nature Communication

  IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE-TPAMI)

  International Journal of Computer Vision (IJCV)

  Medical Image Analysis

  IEEE Transactions on Medical Imaging (IEEE-TMI)

  IEEE Journal of Biomedical And Health Informatics (IEEE-JBHI)

  Medical Physics

  International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)

  Medical Imaging Meets NeurIPS (Med-NeurIPS)

  ICML Workshop on Interpretable ML in Healthcare

Teaching

• Teaching assistant at the Department of Computing, Imperial College London:

  Mathematics for Machine Learning (COMP 70015), Autumn 2020

  Computer Vision (COMP 60006), Spring 2021

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