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PhD projects

see https://www.port.ac.uk/study/postgraduate-research/research-degrees/phd/explore-our-projects/development-of-ai-technologies-to-identify-ocular-disease-0

Personal profile

Biography

I have rich experiences in the areas of computer vision, deep learning, and medical imaging. I have been a main member of some projects including EU FP7 project, EPSRC and Co-I for EU Interreg project.


I am a guest editor in Biomimetics and MDPI.

Teaching Responsibilities

Operating System;

Programming;

Internet of Things;

Robotics;

Big Data

Research Interests

Deep Learning

Computer Vision

Medical Imaging

Robotics

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 15 - Life on Land
  • SDG 17 - Partnerships for the Goals

Education/Academic qualification

Ph.D., University of Portsmouth

External positions

PDRA, University of Liverpool

13 Aug 20181 Sept 2021

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Collaborations and top research areas from the last five years

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  • Dual consistency enabled weakly and semi-supervised optic disc and cup segmentation with dual adaptive graph convolutional networks

    Meng, Y., Zhang, H., Zhao, Y., Gao, D., Hamill, B., Patri, G., Peto, T., Madhusudhan, S. & Zheng, Y., 31 Aug 2022, (Early online) In: IEEE Transactions on Medical Imaging.

    Research output: Contribution to journalArticlepeer-review

    Open Access
    File
    128 Downloads (Pure)
  • Shape-aware weakly/semi-supervised optic disc and cup segmentation with regional/marginal consistency

    Meng, Y., Chen, X., Zhang, H., Zhao, Y., Gao, D., Hamill, B., Patri, G., Peto, T., Madhusudhan, S. & Zheng, Y., 16 Sept 2022, Medical Image Computing and Computer Assisted Intervention – MICCAI 2022: 25th International Conference, Singapore, September 18–22, 2022, Proceedings, Part IV. Wang, L., Dou, Q., Thomas Fletcher, P., Speidel, S. & Li, S. (eds.). Springer Nature, p. 524-534 11 p. (Lecture Notes in Computer Science; vol. 13434).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
    54 Downloads (Pure)
  • Regression of instance boundary by aggregated CNN and GCN

    Meng, Y., Meng, W., Gao, D., Zhao, Y., Yang, X., Huang, X. & Zheng, Y., 7 Nov 2020, Computer Vision – ECCV 2020 - 16th European Conference, 2020, Proceedings. Vedaldi, A., Bischof, H., Brox, T. & Frahm, J.-M. (eds.). Springer, p. 190-207 18 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12353).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
    93 Downloads (Pure)
  • CNN-GCN aggregation enabled boundary regression for biomedical image segmentation

    Meng, Y., Wei, M., Gao, D., Zhao, Y., Yang, X., Huang, X. & Zheng, Y., 29 Sept 2020, Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 - 23rd International Conference, Proceedings. Martel, A. L., Abolmaesumi, P., Stoyanov, D., Mateus, D., Zuluaga, M. A., Zhou, S. K., Racoceanu, D. & Joskowicz, L. (eds.). Springer, p. 352-362 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12264).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
    236 Downloads (Pure)
  • BI-GCN: Boundary-Aware Input-Dependent Graph Convolution Network for biomedical image segmentation

    Meng, Y., Zhang, H., Gao, D., Zhao, Y., Yang, X., Qian, X., Huang, X. & Zheng, Y., 15 Oct 2021, (Accepted for publication) Proceedings of BMVC 2021. British Machine Vision Association

    Research output: Chapter in Book/Report/Conference proceedingConference contribution