Deep snake for real-time instance segmentation S Peng, W Jiang, H Pi, X Li, H Bao, X Zhou Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 322 | 2020 |
Automatic liver segmentation using a statistical shape model with optimal surface detection X Zhang, J Tian, K Deng, Y Wu, X Li IEEE Transactions on Biomedical Engineering 57 (10), 2622-2626, 2010 | 196 | 2010 |
Semi-supervised brain lesion segmentation with an adapted mean teacher model W Cui, Y Liu, Y Li, M Guo, Y Li, X Li, T Wang, X Zeng, C Ye Information Processing in Medical Imaging: 26th International Conference …, 2019 | 181 | 2019 |
Automated delineation of lung tumors from CT images using a single click ensemble segmentation approach Y Gu, V Kumar, LO Hall, DB Goldgof, CY Li, R Korn, C Bendtsen, ... Pattern recognition 46 (3), 692-702, 2013 | 178 | 2013 |
A clinically applicable deep-learning model for detecting intracranial aneurysm in computed tomography angiography images Z Shi, C Miao, UJ Schoepf, RH Savage, DM Dargis, C Pan, X Chai, XL Li, ... Nature communications 11 (1), 6090, 2020 | 109 | 2020 |
Artificial intelligence in the management of intracranial aneurysms: current status and future perspectives Z Shi, B Hu, UJ Schoepf, RH Savage, DM Dargis, CW Pan, XL Li, QQ Ni, ... American Journal of Neuroradiology 41 (3), 373-379, 2020 | 74 | 2020 |
Interactive liver tumor segmentation from ct scans using support vector classification with watershed X Zhang, J Tian, D Xiang, X Li, K Deng 2011 Annual international conference of the IEEE engineering in medicine and …, 2011 | 73 | 2011 |
MMFNet: A multi-modality MRI fusion network for segmentation of nasopharyngeal carcinoma H Chen, Y Qi, Y Yin, T Li, X Liu, X Li, G Gong, L Wang Neurocomputing 394, 27-40, 2020 | 69 | 2020 |
Long-term follow-up of persistent pulmonary pure ground-glass nodules with deep learning–assisted nodule segmentation LL Qi, BT Wu, W Tang, LN Zhou, Y Huang, SJ Zhao, L Liu, M Li, L Zhang, ... European Radiology 30, 744-755, 2020 | 67 | 2020 |
Clinical, conventional CT and radiomic feature-based machine learning models for predicting ALK rearrangement status in lung adenocarcinoma patients L Song, Z Zhu, L Mao, X Li, W Han, H Du, H Wu, W Song, Z Jin Frontiers in Oncology 10, 369, 2020 | 60 | 2020 |
CT-based radiomics to predict the pathological grade of bladder cancer G Zhang, L Xu, L Zhao, L Mao, X Li, Z Jin, H Sun European radiology 30, 6749-6756, 2020 | 49 | 2020 |
A deep network for tissue microstructure estimation using modified LSTM units C Ye, X Li, J Chen Medical image analysis 55, 49-64, 2019 | 49 | 2019 |
Advanced gastric cancer: CT radiomics prediction and early detection of downstaging with neoadjuvant chemotherapy Q Xu, Z Sun, X Li, C Ye, C Zhou, L Zhang, G Lu European radiology 31 (11), 8765-8774, 2021 | 48 | 2021 |
Cascaded generative and discriminative learning for microcalcification detection in breast mammograms F Zhang, L Luo, X Sun, Z Zhou, X Li, Y Yu, Y Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 42 | 2019 |
Development and validation of machine learning prediction model based on computed tomography angiography–derived hemodynamics for rupture status of intracranial aneurysms: a … G Chen, M Lu, Z Shi, S Xia, Y Ren, Z Liu, X Liu, Z Li, L Mao, XL Li, ... European radiology 30, 5170-5182, 2020 | 38 | 2020 |
FAPI-04 PET/CT Using [18F]AlF Labeling Strategy: Automatic Synthesis, Quality Control, and In Vivo Assessment in Patient X Jiang, X Wang, T Shen, Y Yao, M Chen, Z Li, X Li, J Shen, Y Kou, ... Frontiers in Oncology 11, 649148, 2021 | 36 | 2021 |
Exploring transfer learning for gastrointestinal bleeding detection on small-size imbalanced endoscopy images X Li, H Zhang, X Zhang, H Liu, G Xie 2017 39th Annual International Conference of the IEEE Engineering in …, 2017 | 36 | 2017 |
Radiomics based on multiparametric magnetic resonance imaging to predict extraprostatic extension of prostate cancer L Xu, G Zhang, L Zhao, L Mao, X Li, W Yan, Y Xiao, J Lei, H Sun, Z Jin Frontiers in Oncology 10, 940, 2020 | 35 | 2020 |
Lung nodule malignancy prediction using multi-task convolutional neural network X Li, Y Kao, W Shen, X Li, G Xie Medical Imaging 2017: Computer-Aided Diagnosis 10134, 551-557, 2017 | 33 | 2017 |
A trust region method in adaptive finite element framework for bioluminescence tomography B Zhang, X Yang, C Qin, D Liu, S Zhu, J Feng, L Sun, K Liu, D Han, X Ma, ... Optics express 18 (7), 6477-6491, 2010 | 33 | 2010 |