| Modeling Point Clouds with Self-Attention and Gumbel Subset Sampling J Yang, Q Zhang, B Ni, L Li, J Liu, M Zhou, Q Tian CVPR - IEEE Conference on Computer Vision and Pattern Recognition, 3323--3332, 2019 | 417 | 2019 |
| MedMNIST v2 - A large-scale lightweight benchmark for 2D and 3D biomedical image classification J Yang, R Shi, D Wei, Z Liu, L Zhao, B Ke, H Pfister, B Ni Scientific Data (Nature Publishing Group) 10 (1), 41, 2023 | 363 | 2023 |
| MedMNIST Classification Decathlon: A Lightweight AutoML Benchmark for Medical Image Analysis J Yang, R Shi, B Ni ISBI - IEEE International Symposium on Biomedical Imaging, 2021 | 269 | 2021 |
| 3D Deep Learning from CT Scans Predicts Tumor Invasiveness of Subcentimeter Pulmonary Adenocarcinomas W Zhao*, J Yang*, Y Sun, C Li, W Wu, L Jin, Z Yang, B Ni, P Gao, P Wang, ... Cancer Research 78 (24), 6881-6889, 2018 | 182 | 2018 |
| Deep Kinematics Analysis for Monocular 3D Human Pose Estimation J Xu, Z Yu, B Ni, J Yang, X Yang, W Zhang CVPR - IEEE Conference on Computer Vision and Pattern Recognition, 899-908, 2020 | 177 | 2020 |
| 3D Human Action Representation Learning via Cross-View Consistency Pursuit L Li, M Wang, B Ni, H Wang, J Yang, W Zhang CVPR - IEEE Conference on Computer Vision and Pattern Recognition, 2021 | 149 | 2021 |
| Deep-learning-assisted detection and segmentation of rib fractures from CT scans: Development and validation of FracNet L Jin*, J Yang*, K Kuang, B Ni, Y Gao, Y Sun, P Gao, W Ma, M Tan, ... eBioMedicine (The Lancet Discovery Science) 62, 103106, 2020 | 123 | 2020 |
| Dynamic points agglomeration for hierarchical point sets learning J Liu, B Ni, C Li, J Yang, Q Tian ICCV - IEEE International Conference on Computer Vision, 7546-7555, 2019 | 113 | 2019 |
| Adversarial attack and defense on point sets J Yang, Q Zhang, R Fang, B Ni, J Liu, Q Tian arXiv preprint arXiv:1902.10899, 2019 | 108 | 2019 |
| Toward automatic prediction of EGFR mutation status in pulmonary adenocarcinoma with 3D deep learning W Zhao*, J Yang*, B Ni, D Bi, Y Sun, M Xu, X Zhu, C Li, L Jin, P Gao, ... Cancer Medicine, 2019 | 100 | 2019 |
| Reinventing 2D Convolutions for 3D Images J Yang, X Huang, Y He, J Xu, C Yang, G Xu, B Ni JBHI - IEEE Journal of Biomedical and Health Informatics, 2021 | 86 | 2021 |
| Learning Black-Box Attackers with Transferable Priors and Query Feedback J Yang, Y Jiang, X Huang, B Ni, C Zhao NeurIPS - Neural Information Processing Systems, 2020 | 62 | 2020 |
| A multi-omics-based serial deep learning approach to predict clinical outcomes of single-agent anti-PD-1/PD-L1 immunotherapy in advanced stage non-small-cell lung cancer Y Yang*, J Yang*, L Shen*, J Chen, L Xia, B Ni, L Ge, Y Wang, S Lu American Journal of Translational Research 13 (2), 743, 2021 | 60 | 2021 |
| Shape Self-Correction for Unsupervised Point Cloud Understanding Y Chen, J Liu, B Ni, H Wang, J Yang, N Liu, T Li, Q Tian ICCV - IEEE International Conference on Computer Vision, 8382-8391, 2021 | 43 | 2021 |
| DigestPath: A benchmark dataset with challenge review for the pathological detection and segmentation of digestive-system Q Da, X Huang, Z Li, Y Zuo, C Zhang, J Liu, W Chen, J Li, D Xu, Z Hu, H Yi, ... Medical Image Analysis 80, 102485, 2022 | 42 | 2022 |
| Relational Learning between Multiple Pulmonary Nodules via Deep Set Attention Transformers J Yang, H Deng, X Huang, B Ni, Y Xu ISBI - IEEE International Symposium on Biomedical Imaging, 1875-1878, 2020 | 28 | 2020 |
| ImplicitAtlas: Learning Deformable Shape Templates in Medical Imaging J Yang, U Wickramasinghe, B Ni, P Fua CVPR - IEEE Conference on Computer Vision and Pattern Recognition, 15861-15871, 2022 | 23 | 2022 |
| Asymmetric 3D Context Fusion for Universal Lesion Detection J Yang, Y He, K Kuang, Z Lin, H Pfister, B Ni MICCAI - International Conference on Medical Image Computing and Computer …, 2021 | 23 | 2021 |
| AlignShift: Bridging the Gap of Imaging Thickness in 3D Anisotropic Volumes J Yang, Y He, X Huang, J Xu, X Ye, G Tao, B Ni MICCAI - International Conference on Medical Image Computing and Computer …, 2020 | 23 | 2020 |
| Convolution kernel and iterative reconstruction affect the diagnostic performance of radiomics and deep learning in lung adenocarcinoma pathological subtypes W Zhao, W Zhang, Y Sun, Y Ye, J Yang, W Chen, P Gao, J Li, C Li, L Jin, ... Thoracic Cancer 10 (10), 1893-1903, 2019 | 21 | 2019 |
Donglai WeiAssistant Professor, Boston College在 bc.edu 的电子邮件经过验证
