Diagnosis
We proposed enhancement and diagnosis frameworks based on unsupervised multi-modal atlas mining and transfer cyclic feature learning. Developed methods including diversity-aware auto-focusing, kernel distillation focus, cross-modal virtual staining, achieving millisecond-level super-resolution imaging and in vivo pathological semantic transfer.
Related Papers
- C. Zhang, K. Wang, Y. Gu, Beyond Low-Rank Tuning: Model Prior-Guided Rank Allocation for Effective Transfer in Low-Data and Large-Gap Regimes, IEEE International Conference on Computer Vision (ICCV), 2025 — code
- C. Zhang, H. Zheng, X. You, Y. Zheng, Y. Gu, PASS: Test-Time Prompting to Adapt Styles and Semantic Shapes in Medical Image Segmentation, IEEE Transactions on Medical Imaging (TMI), 2025 — code
- C. Zhang, Y. Yang, H. Zheng, Y. Huang, Y. Zheng, Y. Gu, Normalization as a Shortcut to Adaptation: A Unified Framework for Transferability Measurement in Medical Image Analysis, Pattern Recognition (PR), 2024 — code
- C. Zhang, H. Zheng, X. You, Y. Zheng, Y. Gu, Dive into the Details of Self-supervised Learning for Medical Image Analysis, Medical Image Analysis (MedIA), 2023 — code
- C. Zhang, G.-Z. Yang, Y. Gu, Constrastive Adversarial Learning for Unsupervised Endomicroscopy Image Super-Resolution, IEEE Journal of Biomedical and Health Informatics (JBHI), 2023
- Y. Gu, Y. Xu, J. Yang, W. Xue, G.-Z. Yang, Towards Robust Feature Embedding for Endomicroscopy Image Classification, IEEE Transactions on Medical Imaging (TMI), 2022
- Y. Gu, K. Vyas, M. Shen, J. Yang, G.-Z. Yang, Deep Graph-Based Multimodal Feature Embedding for Endomicroscopy Image Retrieval, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020
- Y. Gu, K. Vyas, J. Yang, G.-Z. Yang, Transfer Recurrent Feature Learning for Endomicroscopy Image Recognition, IEEE Transactions on Medical Imaging (TMI), 2019
- C. Zhang, Y. Gu, J. Yang, G.-Z. Yang, Diversity-Aware Label Distribution Learning for Microscopy Auto Focusing, ICRA (with RAL submission), 2021