| Monai: An open-source framework for deep learning in healthcare MJ Cardoso, W Li, R Brown, N Ma, E Kerfoot, Y Wang, B Murrey, ... arXiv preprint arXiv:2211.02701, 2022 | 622 | 2022 |
| DeepHarmony: A deep learning approach to contrast harmonization across scanner changes BE Dewey, C Zhao, JC Reinhold, A Carass, KC Fitzgerald, ES Sotirchos, ... Magnetic resonance imaging 64, 160-170, 2019 | 237 | 2019 |
| Unpaired brain MR-to-CT synthesis using a structure-constrained CycleGAN H Yang, J Sun, A Carass, C Zhao, J Lee, Z Xu, J Prince Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2018 | 205 | 2018 |
| Unsupervised MR-to-CT synthesis using structure-constrained CycleGAN H Yang, J Sun, A Carass, C Zhao, J Lee, JL Prince, Z Xu IEEE transactions on medical imaging 39 (12), 4249-4261, 2020 | 169 | 2020 |
| SMORE: A Self-supervised Anti-aliasing and Super-resolution Algorithm for MRI Using Deep Learning C Zhao, BE Dewey, DL Pham, PA Calabresi, DS Reich, JL Prince IEEE Transactions on Medical Imaging, 2020 | 165 | 2020 |
| Dints: Differentiable neural network topology search for 3d medical image segmentation Y He, D Yang, H Roth, C Zhao, D Xu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 112 | 2021 |
| Nvidia flare: Federated learning from simulation to real-world HR Roth, Y Cheng, Y Wen, I Yang, Z Xu, YT Hsieh, K Kersten, A Harouni, ... arXiv preprint arXiv:2210.13291, 2022 | 105 | 2022 |
| Applications of a deep learning method for anti-aliasing and super-resolution in MRI C Zhao, M Shao, A Carass, H Li, BE Dewey, LM Ellingsen, J Woo, ... Magnetic resonance imaging 64, 132-141, 2019 | 105 | 2019 |
| Generative ai for medical imaging: extending the monai framework WHL Pinaya, MS Graham, E Kerfoot, PD Tudosiu, J Dafflon, V Fernandez, ... arXiv preprint arXiv:2307.15208, 2023 | 87 | 2023 |
| Whole brain segmentation and labeling from CT using synthetic MR images C Zhao, A Carass, J Lee, Y He, JL Prince Machine Learning in Medical Imaging: 8th International Workshop, MLMI 2017 …, 2017 | 77 | 2017 |
| Closing the generalization gap of cross-silo federated medical image segmentation A Xu, W Li, P Guo, D Yang, HR Roth, A Hatamizadeh, C Zhao, D Xu, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 75 | 2022 |
| Self super-resolution for magnetic resonance images using deep networks C Zhao, A Carass, BE Dewey, JL Prince 2018 IEEE 15th international symposium on biomedical imaging (ISBI 2018 …, 2018 | 74 | 2018 |
| A deep learning based anti-aliasing self super-resolution algorithm for MRI C Zhao, A Carass, BE Dewey, J Woo, J Oh, PA Calabresi, DS Reich, ... Medical image computing and computer assisted intervention–mICCAI 2018: 21st …, 2018 | 61 | 2018 |
| Auto-fedrl: Federated hyperparameter optimization for multi-institutional medical image segmentation P Guo, D Yang, A Hatamizadeh, A Xu, Z Xu, W Li, C Zhao, D Xu, ... European Conference on Computer Vision, 437-455, 2022 | 59 | 2022 |
| Towards topological correct segmentation of macular OCT from cascaded FCNs Y He, A Carass, Y Yun, C Zhao, BM Jedynak, SD Solomon, S Saidha, ... Fetal, Infant and Ophthalmic Medical Image Analysis: International Workshop …, 2017 | 54 | 2017 |
| Fair federated medical image segmentation via client contribution estimation M Jiang, HR Roth, W Li, D Yang, C Zhao, V Nath, D Xu, Q Dou, Z Xu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 49 | 2023 |
| Multi-atlas-based CT synthesis from conventional MRI with patch-based refinement for MRI-based radiotherapy planning J Lee, A Carass, A Jog, C Zhao, JL Prince Medical Imaging 2017: Image Processing 10133, 434-439, 2017 | 47 | 2017 |
| Biomedical image analysis competitions: The state of current participation practice M Eisenmann, A Reinke, V Weru, MD Tizabi, F Isensee, TJ Adler, ... arXiv preprint arXiv:2212.08568, 2022 | 32 | 2022 |
| Deep harmonization of inconsistent MR data for consistent volume segmentation BE Dewey, C Zhao, A Carass, J Oh, PA Calabresi, PCM van Zijl, JL Prince International Workshop on Simulation and Synthesis in Medical Imaging, 20-30, 2018 | 24 | 2018 |
| Lamp: Large deep nets with automated model parallelism for image segmentation W Zhu, C Zhao, W Li, H Roth, Z Xu, D Xu Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 23 | 2020 |
Jerry L. PrinceProfessor of Electrical and Computer Engineering, Johns Hopkins UniversityZweryfikowany adres z jhu.edu