| CT super-resolution GAN constrained by the identical, residual, and cycle learning ensemble (GAN-CIRCLE) C You, G Li, Y Zhang, X Zhang, H Shan, M Li, S Ju, Z Zhao, Z Zhang, ... IEEE transactions on medical imaging 39 (1), 188-203, 2019 | 460 | 2019 |
| Segment anything in medical images J Ma, Y He, F Li, L Han, C You, B Wang Nature communications, 2023 | 364 | 2023 |
| Structurally-sensitive multi-scale deep neural network for low-dose CT denoising C You, Q Yang, H Shan, L Gjesteby, G Li, S Ju, Z Zhang, Z Zhao, Y Zhang, ... IEEE access 6, 41839-41855, 2018 | 232 | 2018 |
| SimCVD: Simple contrastive voxel-wise representation distillation for semi-supervised medical image segmentation C You, Y Zhou, R Zhao, L Staib, JS Duncan IEEE Transactions on Medical Imaging, 2022, 2022 | 174 | 2022 |
| Momentum contrastive voxel-wise representation learning for semi-supervised volumetric medical image segmentation C You, R Zhao, L Staib, JS Duncan In Proceedings of MICCAI 2022 (early accepted), 2021 | 96 | 2021 |
| NuSeT: A deep learning tool for reliably separating and analyzing crowded cells L Yang, RP Ghosh, JM Franklin, S Chen, C You, RR Narayan, ... PLoS computational biology 16 (9), e1008193, 2020 | 93 | 2020 |
| Auto-Encoding Knowledge Graph for Unsupervised Medical Report Generation F Liu, C You, X Wu, S Ge, S Wang, X Sun In Proceedings of NeurIPS 2021, 2021 | 91 | 2021 |
| Class-aware adversarial transformers for medical image segmentation C You, R Zhao, F Liu, S Chinchali, U Topcu, L Staib, JS Duncan In Proceedings of NeurIPS 2022, 2022 | 86 | 2022 |
| Low-dose CT via deep CNN with skip connection and network-in-network C You, L Yang, Y Zhang, G Wang Developments in X-Ray tomography XII 11113, 429-434, 2019 | 58 | 2019 |
| Super-resolution MRI through deep learning Q Lyu*, C You*, H Shan, G Wang arXiv preprint arXiv:1810.06776 (* denotes equal contribution), 2018 | 56 | 2018 |
| Super-resolution MRI and CT through GAN-CIRCLE Q Lyu*, C You*, H Shan, Y Zhang, G Wang Developments in X-ray tomography XII (* denotes equal contribution), 2019 | 53 | 2019 |
| Unsupervised wasserstein distance guided domain adaptation for 3d multi-domain liver segmentation C You, J Yang, J Chapiro, JS Duncan Interpretable and Annotation-Efficient Learning for Medical Image Computing …, 2020 | 47 | 2020 |
| Kergnns: Interpretable graph neural networks with graph kernels A Feng, C You, S Wang, L Tassiulas Proceedings of the AAAI conference on artificial intelligence 36 (6), 6614-6622, 2022 | 46 | 2022 |
| Self-supervised Contrastive Cross-Modality Representation Learning for Spoken Question Answering C You, N Chen, Y Zou In Findings of EMNLP 2021, 2021 | 46 | 2021 |
| Bootstrapping semi-supervised medical image segmentation with anatomical-aware contrastive distillation C You, W Dai, L Staib, JS Duncan International Conference on Information Processing in Medical Imaging (IPMI …, 2022 | 44 | 2022 |
| Deep learning based high-resolution reconstruction of trabecular bone microstructures from low-resolution CT scans using GAN-CIRCLE I Guha, SA Nadeem, C You, X Zhang, SM Levy, G Wang, JC Torner, ... Proceedings of SPIE--the International Society for Optical Engineering 11317, 2020 | 44 | 2020 |
| Undistillable: Making A Nasty Teacher That CANNOT teach students H Ma, T Chen, TK Hu, C You, X Xie, Z Wang International Conference on Learning Representations (ICLR), 2021 | 37 | 2021 |
| Mine your own anatomy: Revisiting medical image segmentation with extremely limited labels C You, W Dai, F Liu, Y Min, H Su, X Zhang, X Li, DA Clifton, L Staib, ... arXiv preprint arXiv:2209.13476, 2022 | 34 | 2022 |
| Towards data distillation for end-to-end spoken conversational question answering C You, N Chen, F Liu, D Yang, Y Zou arXiv preprint arXiv:2010.08923, 2020 | 34 | 2020 |
| Knowledge distillation for improved accuracy in spoken question answering C You, N Chen, Y Zou In Proceedings of ICASSP 2021, 7793-7797, 2021 | 33 | 2021 |
James S. DuncanEbenezer K. Hunt Professor of Biomedical Engineering, Radiology, Electr. Engr., Yale UniversityVerified email at yale.edu
