Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks L Yu, H Chen, Q Dou, J Qin, PA Heng IEEE Transactions on Medical Imaging, 2017 | 1102 | 2017 |
VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images H Chen, Q Dou, L Yu, J Qin, PA Heng NeuroImage 170, 446-455, 2018 | 937* | 2018 |
Automatic detection of cerebral microbleeds from MR images via 3D convolutional neural networks Q Dou, H Chen, L Yu, L Zhao, J Qin, D Wang, VCT Mok, L Shi, PA Heng IEEE transactions on medical imaging 35 (5), 1182-1195, 2016 | 765 | 2016 |
Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation L Yu, S Wang, X Li, CW Fu, PA Heng International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 759 | 2019 |
DCAN: deep contour-aware networks for accurate gland segmentation H Chen, X Qi, L Yu, PA Heng Proceedings of the IEEE conference on Computer Vision and Pattern …, 2016 | 729 | 2016 |
Multilevel contextual 3-D CNNs for false positive reduction in pulmonary nodule detection Q Dou, H Chen, L Yu, J Qin, PA Heng IEEE Transactions on Biomedical Engineering 64 (7), 1558-1567, 2016 | 648 | 2016 |
Pu-net: Point cloud upsampling network L Yu, X Li, CW Fu, D Cohen-Or, PA Heng Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 621 | 2018 |
3D deeply supervised network for automated segmentation of volumetric medical images Q Dou, L Yu, H Chen, Y Jin, X Yang, J Qin, PA Heng Medical image analysis 41, 40-54, 2017 | 611 | 2017 |
DCAN: Deep contour-aware networks for object instance segmentation from histology images H Chen, X Qi, L Yu, Q Dou, J Qin, PA Heng Medical image analysis 36, 135-146, 2017 | 501 | 2017 |
Transformation-Consistent Self-Ensembling Model for Semisupervised Medical Image Segmentation X Li, L Yu, H Chen, CW Fu, L Xing, PA Heng IEEE Transactions on Neural Networks and Learning Systems, 2020 | 429 | 2020 |
3D deeply supervised network for automatic liver segmentation from CT volumes Q Dou, H Chen, Y Jin, L Yu, J Qin, PA Heng Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016 | 427 | 2016 |
nnformer: Volumetric medical image segmentation via a 3d transformer HY Zhou, J Guo, Y Zhang, X Han, L Yu, L Wang, Y Yu IEEE Transactions on Image Processing, 2023 | 418* | 2023 |
Volumetric ConvNets with mixed residual connections for automated prostate segmentation from 3D MR images L Yu, X Yang, H Chen, J Qin, PA Heng Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 415 | 2017 |
Comparative validation of polyp detection methods in video colonoscopy: results from the MICCAI 2015 endoscopic vision challenge J Bernal, N Tajkbaksh, FJ Sanchez, BJ Matuszewski, H Chen, L Yu, ... IEEE transactions on medical imaging 36 (6), 1231-1249, 2017 | 409 | 2017 |
CANet: cross-disease attention network for joint diabetic retinopathy and diabetic macular edema grading X Li, X Hu, L Yu, L Zhu, CW Fu, PA Heng IEEE transactions on medical imaging 39 (5), 1483-1493, 2019 | 338 | 2019 |
Ec-net: an edge-aware point set consolidation network L Yu, X Li, CW Fu, D Cohen-Or, PA Heng Proceedings of the European conference on computer vision (ECCV), 386-402, 2018 | 278 | 2018 |
SV-RCNet: workflow recognition from surgical videos using recurrent convolutional network Y Jin, Q Dou, H Chen, L Yu, J Qin, CW Fu, PA Heng IEEE transactions on medical imaging 37 (5), 1114-1126, 2017 | 268 | 2017 |
MS-Net: Multi-Site Network for Improving Prostate Segmentation with Heterogeneous MRI Data Q Liu, Q Dou, L Yu, PA Heng IEEE Transactions on Medical Imaging, 2020 | 262 | 2020 |
Patch-based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentation S Wang, L Yu, X Yang, CW Fu, PA Heng IEEE transactions on medical imaging, 2019 | 252 | 2019 |
Integrating Online and Offline Three-Dimensional Deep Learning for Automated Polyp Detection in Colonoscopy Videos L Yu, H Chen, Q Dou, J Qin, PA Heng IEEE journal of biomedical and health informatics, 2017 | 252 | 2017 |