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Chenyu You
Chenyu You
Assistant Professor of Applied Mathematics & Statistics and Computer Science, Stony Brook University
在 stonybrook.edu 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Segment anything in medical images
J Ma, Y He, F Li, L Han, C You, B Wang
Nature Communications 15 (1), 654, 2024
7092024
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
4902019
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
2462018
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 41 (9), 2228-2237, 2022
1992022
Auto-encoding knowledge graph for unsupervised medical report generation
F Liu, C You, X Wu, S Ge, X Sun
Advances in Neural Information Processing Systems 34, 16266-16279, 2021
1132021
Momentum contrastive voxel-wise representation learning for semi-supervised volumetric medical image segmentation
C You, R Zhao, LH Staib, JS Duncan
International Conference on Medical Image Computing and Computer-Assisted …, 2022
1072022
Class-aware adversarial transformers for medical image segmentation
C You, R Zhao, F Liu, S Dong, S Chinchali, U Topcu, L Staib, J Duncan
Advances in Neural Information Processing Systems 35, 29582-29596, 2022
1052022
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
982020
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
622022
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
622019
Super-resolution MRI through deep learning
Q Lyu, C You, H Shan, G Wang
arXiv preprint arXiv:1810.06776, 2018
602018
Bootstrapping semi-supervised medical image segmentation with anatomical-aware contrastive distillation
C You, W Dai, Y Min, L Staib, JS Duncan
International conference on information processing in medical imaging, 641-653, 2023
592023
Super-resolution MRI and CT through GAN-circle
Q Lyu, C You, H Shan, Y Zhang, G Wang
Developments in X-ray tomography XII 11113, 202-208, 2019
572019
Self-supervised contrastive cross-modality representation learning for spoken question answering
C You, N Chen, Y Zou
arXiv preprint arXiv:2109.03381, 2021
562021
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
542020
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
492020
Incremental learning meets transfer learning: Application to multi-site prostate mri segmentation
C You, J Xiang, K Su, X Zhang, S Dong, J Onofrey, L Staib, JS Duncan
International Workshop on Distributed, Collaborative, and Federated Learning …, 2022
472022
Rethinking semi-supervised medical image segmentation: A variance-reduction perspective
C You, W Dai, Y Min, F Liu, D Clifton, SK Zhou, L Staib, J Duncan
Advances in neural information processing systems 36, 2024
452024
Knowledge distillation for improved accuracy in spoken question answering
C You, N Chen, Y Zou
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
432021
Undistillable: Making a nasty teacher that cannot teach students
H Ma, T Chen, TK Hu, C You, X Xie, Z Wang
arXiv preprint arXiv:2105.07381, 2021
432021
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