Y. Gu
, C. Gu, J. Yang, J. Sun and G.-Z. Yang, Vision-Kinematics-Interaction for Robotic-Assisted Bronchoscopy Navigation, IEEE Transactions on Medical Imaging (TMI)
, 41(12): 3600-3610, 2022.Y. Gu
, Y. Xu, J. Yang, W. Xue and G.-Z. Yang, Towards Robust Feature Embedding for Endomicroscopy Image Classification, IEEE Transactions on Medical Imaging (TMI)
, 41(11): 3242-3252, 2022.Y. Gu
, K. Vyas, J. Yang, and G.-Z. Yang, Transfer Recurrent Feature Learning for Endomicroscopy Image Recognition, IEEE Transactions on Medical Imaging (TMI)
, 38(3): 791-801, 2019.Y. Gu
, B. Walter, J. Yang, A. Meining, and G.-Z. Yang, “Triplet Feature Learning on Endoscopic Video Manifold for Online GastroIntestinal Image Retargeting,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
, 2019, pp. 38–46.Y. Gu
, K. Vyas, J. Yang, and G.-Z. Yang, “Weakly supervised representation learning for endomicroscopy image analysis,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
, 2018, pp. 326–334. Early Accepted, Student Travel Award
Y. Gu
, K. Vyas, J. Yang, and G.-Z. Yang, “Unsupervised feature learning for endomicroscopy image retrieval,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
, 2017, pp. 64–71.- Xin You, Junjun He, Jie Yang,
Y. Gu
, Learning with Explicit Shape Priors for Medical Image Segmentation, IEEE Transactions on Medical Imaging (TMI)
, 2024. - Puyang Wang, Dazhou Guo, Dandan Zheng, Minghui Zhang, Haogang Yu, Xin Sun, Jia Ge,
Y. Gu
, Le Lu, Xianghua Ye, Dakai Jin, Accurate Airway Tree Segmentation in CT Scans via Anatomy-aware Multi-class Segmentation and Topology-guided Iterative Learning, IEEE Transactions on Medical Imaging (TMI)
, 2024. - Chao Xia, Jiyue Wang, Yulei Qin, Juan Wen, Zhaojiang Liu, Ning Song, Lingqian Wu, Bing Chen,
Y. Gu
, Jie Yang, KaryoNet: An End-to-End Combinatorial Optimization Method for Chromosome Recognition in Metaphase Cell Images, IEEE Transactions on Medical Imaging (TMI)
, 42(10): 2899-2911, 2023. - W. Yu, H. Zheng,
Y. Gu
, F. Xie, J. Yang, J. Sun and G.-Z. Yang, TNN: Tree Neural Network for Airway Anatomical Labeling, IEEE Transactions on Medical Imaging (TMI)
, 42(1):103-118, 2023 - H Zheng, Y Qin,
Y. Gu
, F Xie, J Yang, J Sun, GZ Yang, Alleviating class-wise gradient imbalance for pulmonary airway segmentation, IEEE Transactions on Medical Imaging (TMI)
, 40(9): 2452-2462, 2021. - Y Qin, H Zheng,
Y. Gu
, X Huang, J Yang, L Wang, F Yao, YM Zhu, G.Z Yang, Learning tubule-sensitive CNNs for pulmonary airway and artery-vein segmentation in CT, IEEE Transactions on Medical Imaging (TMI)
, 40(6): 1603-1617, 2021 - Yang Nan, ..., Minghui Zhang,
Y. Gu
, Hanxiao Zhang,..., Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge, Medical Image Analysis (MedIA)
, 2024. - H. Zhang, L. Chen, X. Gu, M. Zhang, Y. Qin, F. Yao, Z. Wang,
Y. Gu
and G.-Z. Yang, Trustworthy learning with (un)sure annotation for lung nodule diagnosis with CT, Medical Image Analysis (MedIA)
, 83: 102627, 2023 - M. Zhang,...,
Y. Gu
, Multi-site, Multi-domain Airway Tree Modeling, Medical Image Analysis (MedIA)
, 90:102957, 2023 - C. Zhang, H. Zheng,
Y. Gu
, Dive into the Details of Self-supervised Learning for Medical Image Analysis, Medical Image Analysis (MedIA)
, 89:102879, 2023 - M. Zhang, H. Zhang, X. You, G.-Z. Yang,
Y. Gu
, “Implicit Representation Embraces Challenging Attributes of Pulmonary Airway Tree Structures”, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
, 2024. - X. You,
Y. Gu
, Y. Wu, M. Zhang, M. Ding, Y. Yu, J. Yang, “Semantic difference guidance for the uncertain boundary segmentation of CT left atrium appendage”,International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
, 2023. - H. Yue,
Y. Gu
“TCL: Triplet Consistent Learning for Odometry Estimation of Monocular Endoscope”,International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
, 2023. - Y. Yang, M. Wei, J. He, J. Yang, J. Ye and
Y. Gu
, “Pick the Best Pre-trained Model: Towards Transferability Estimation For Medical Image Segmentation”,International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
, 2023, Early Accepted
. - W. Yu, H. Zheng,
Y. Gu
, F. Xie, J. Sun, J. Yang, “AirwayFormer: Structure-Aware Boundary-Adaptive Transformers for Airway Anatomical Labeling”,International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
, 2023, Early Accepted
. - M. Zhang, H. Zhang, G.-Z. Yang,
Y. Gu
, “CFDA: Collaborative Feature Disentanglement and Augmentation for Pulmonary Airway Tree Modeling of COVID-19 CTs,” International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
, 2022, Early Accepted, Student Travel Award
. - C. Xia, J. Wang, Y. Qin,
Y. Gu
, B. Chen, J. Yang, “An End-to-End Combinatorial Optimization Method for R-band Chromosome Recognition with Grouping Guided Attention,” International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
, 2022, Early Accepted
. - H Zheng, Y Qin,
Y. Gu
, F Xie, J Sun, J Yang, GZ Yang, “Refined Local-imbalance-based Weight for Airway Segmentation in CT,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
, 2021, pp. 410–419. - H. Zhang,
Y. Gu
, Y. Qin, F. Yao, and G.-Z. Yang, “Learning with sure data for nodule-level lung cancer prediction,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
, 2020, pp. 570–578. - H. Zheng, Z. Zhuang, Y. Qin,
Y. Gu
, J. Yang, and G.-Z. Yang, “Weakly supervised deep learning for breast cancer segmentation with coarse annotations,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
, 2020, pp. 450–459. - Y Qin, H Zheng,
Y. Gu
, X Huang, J Yang, L Wang, YM Zhu, “Learning bronchiole-sensitive airway segmentation CNNs by feature recalibration and attention distillation,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
, 2020, pp. 221–231. Early Accepted
- Y Qin, M Chen, H Zheng,
Y. Gu
, M Shen, J Yang, X Huang, YM Zhu, GZ Yang, “Airwaynet: a voxel-connectivity aware approach for accurate airway segmentation using convolutional neural networks,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
, 2019, pp. 212–220. - H. Zheng,
Y. Gu
, Y. Qin, X. Huang, J. Yang, G.-Z. Yang, “Small lesion classification in dynamic contrast enhancement MRI for breast cancer early detection,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
, 2018, pp. 410–419.
