Fuping Wu
PhD
Researcher in Medical Image Analysis
Fuping is a postdoctoral researcher in the Bartlomiej Papiez group, studying the integration of medical imaging and genetic data using machine learning for identification of micro and macro vascular disease targets. The project is a part of an Oxford – Novo Nordisk Collaboration.
Fuping has been studying medical image analysis since his PhD, and is mainly interested in image segmentation and classification using few labeled data, especially using domain adaptation and semi-supervised learning methods. He is also interested in federated/incremental learning.
Recent publications
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DiffuSeg: Domain-driven Diffusion for Medical Image Segmentation
Journal article
Zhang L. et al, (2025), IEEE Journal of Biomedical and Health Informatics
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MT-CooL: Multi-Task Cooperative Learning via Flat Minima Searching
Journal article
Wu F. et al, (2024), IEEE Transactions on Medical Imaging
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Labelling with dynamics: A data-efficient learning paradigm for medical image segmentation.
Journal article
Mo Y. et al, (2024), Med Image Anal, 95
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Multi-target landmark detection with incomplete images via reinforcement learning and shape prior embedding.
Journal article
Wan K. et al, (2023), Med Image Anal, 89
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A New Framework of Swarm Learning Consolidating Knowledge From Multi-Center Non-IID Data for Medical Image Segmentation.
Journal article
Gao Z. et al, (2023), IEEE Trans Med Imaging, 42, 2118 - 2129