| Implementation of medical image segmentation in CUDA L Pan, L Gu, J Xu 2008 International Conference on Information Technology and Applications in …, 2008 | 96 | 2008 |
| Multi-label ocular disease classification with a dense correlation deep neural network J He, C Li, J Ye, Y Qiao, L Gu Biomedical Signal Processing and Control 63, 102167, 2021 | 82 | 2021 |
| An improved level set for liver segmentation and perfusion analysis in MRIs G Chen, L Gu, L Qian, J Xu IEEE Transactions on Information Technology in Biomedicine 13 (1), 94-103, 2008 | 68 | 2008 |
| Stu-net: Scalable and transferable medical image segmentation models empowered by large-scale supervised pre-training Z Huang, H Wang, Z Deng, J Ye, Y Su, H Sun, J He, Y Gu, L Gu, S Zhang, ... arXiv preprint arXiv:2304.06716, 2023 | 67 | 2023 |
| Automatic detection of coronary artery stenosis by convolutional neural network with temporal constraint W Wu, J Zhang, H Xie, Y Zhao, S Zhang, L Gu Computers in biology and medicine 118, 103657, 2020 | 66 | 2020 |
| GPU-based volume rendering for medical image visualization Y Heng, L Gu 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, 5145-5148, 2006 | 63 | 2006 |
| A hybrid deformable model for real-time surgical simulation B Zhu, L Gu Computerized Medical Imaging and Graphics 36 (5), 356-365, 2012 | 61 | 2012 |
| Revisiting nnu-net for iterative pseudo labeling and efficient sliding window inference Z Huang, H Wang, J Ye, J Niu, C Tu, Y Yang, S Du, Z Deng, L Gu, J He MICCAI Challenge on Fast and Low-Resource Semi-supervised Abdominal Organ …, 2022 | 59 | 2022 |
| A homotopy-based sparse representation for fast and accurate shape prior modeling in liver surgical planning G Wang, S Zhang, H Xie, DN Metaxas, L Gu Medical image analysis 19 (1), 176-186, 2015 | 52 | 2015 |
| Dense correlation network for automated multi-label ocular disease detection with paired color fundus photographs C Li, J Ye, J He, S Wang, Y Qiao, L Gu 2020 IEEE 17th international symposium on biomedical imaging (ISBI), 1-4, 2020 | 50 | 2020 |
| Recognition of abdominal organs using 3D mathematical morphology H Fujimoto, L Gu, T Kaneko Systems and Computers in Japan 33 (8), 75-83, 2002 | 48 | 2002 |
| Flow instability detected in ruptured versus unruptured cerebral aneurysms at the internal carotid artery L Xu, F Liang, L Gu, H Liu Journal of biomechanics 72, 187-199, 2018 | 41 | 2018 |
| Weakly supervised vessel segmentation in X-ray angiograms by self-paced learning from noisy labels with suggestive annotation J Zhang, G Wang, H Xie, S Zhang, N Huang, S Zhang, L Gu Neurocomputing 417, 114-127, 2020 | 40 | 2020 |
| Pulmonary nodule detection in CT images based on shape constraint CV model B Wang, X Tian, Q Wang, Y Yang, H Xie, S Zhang, L Gu Medical physics 42 (3), 1241-1254, 2015 | 38 | 2015 |
| A novel remote‐controlled robotic system for cerebrovascular intervention H Shen, C Wang, L Xie, S Zhou, L Gu, H Xie The International Journal of Medical Robotics and Computer Assisted Surgery …, 2018 | 37 | 2018 |
| Real-time simulation of deformable soft tissue based on mass-spring and medial representation S Zhang, L Gu, P Huang, J Xu International Workshop on Computer Vision for Biomedical Image Applications …, 2005 | 35 | 2005 |
| A robust and real-time vascular intervention simulation based on Kirchhoff elastic rod M Luo, H Xie, L Xie, P Cai, L Gu Computerized medical imaging and graphics 38 (8), 735-743, 2014 | 34 | 2014 |
| A new segmentation framework based on sparse shape composition in liver surgery planning system G Wang, S Zhang, F Li, L Gu Medical physics 40 (5), 051913, 2013 | 34 | 2013 |
| A novel robotic system for vascular intervention: principles, performances, and applications H Shen, C Wang, L Xie, S Zhou, L Gu, H Xie International journal of computer assisted radiology and surgery 14, 671-683, 2019 | 32 | 2019 |
| A novel active learning framework for classification: Using weighted rank aggregation to achieve multiple query criteria Y Zhao, Z Shi, J Zhang, D Chen, L Gu Pattern Recognition 93, 581-602, 2019 | 31 | 2019 |
