| UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation Y Gao, M Zhou, D Metaxas Medical Image Computing and Computer Assisted Intervention, 61-71, 2021 | 525 | 2021 |
| A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark Y Gao, M Zhou, D Liu, D Metaxas arXiv preprint arXiv:2203.00131, 2022 | 101 | 2022 |
| FocusNet: imbalanced large and small organ segmentation with an end-to-end deep neural network for head and neck CT images Y Gao, R Huang, M Chen, Z Wang, J Deng, Y Chen, Y Yang, J Zhang, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 85 | 2019 |
| FocusNetv2: Imbalanced large and small organ segmentation with adversarial shape constraint for head and neck CT images Y Gao, R Huang, Y Yang, J Zhang, K Shao, C Tao, Y Chen, DN Metaxas, ... Medical Image Analysis 67, 101831, 2021 | 83 | 2021 |
| Crossnorm and selfnorm for generalization under distribution shifts Z Tang, Y Gao, Y Zhu, Z Zhang, M Li, DN Metaxas Proceedings of the IEEE/CVF International Conference on Computer Vision, 52-61, 2021 | 78* | 2021 |
| OnlineAugment: Online Data Augmentation with Less Domain Knowledge Z Tang, Y Gao, L Karlinsky, P Sattigeri, R Feris, D Metaxas European Conference on Computer Vision 2020, 2020 | 78 | 2020 |
| Visual prompt tuning for test-time domain adaptation Y Gao, X Shi, Y Zhu, H Wang, Z Tang, X Zhou, M Li, DN Metaxas arXiv preprint arXiv:2210.04831, 2022 | 76 | 2022 |
| Vertebrae identification and localization utilizing fully convolutional networks and a hidden Markov model Y Chen, Y Gao, K Li, L Zhao, J Zhao IEEE Transactions on Medical Imaging 39 (2), 387-399, 2019 | 62 | 2019 |
| Transfusion: multi-view divergent fusion for medical image segmentation with transformers D Liu, Y Gao, Q Zhangli, L Han, X He, Z Xia, S Wen, Q Chang, Z Yan, ... International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 36 | 2022 |
| Enabling data diversity: efficient automatic augmentation via regularized adversarial training Y Gao, Z Tang, M Zhou, D Metaxas International Conference on Information Processing in Medical Imaging, 85-97, 2021 | 27 | 2021 |
| Training Like a Medical Resident: Context-Prior Learning Toward Universal Medical Image Segmentation Y Gao, Z Li, D Liu, M Zhou, S Zhang, DN Metaxas The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024, 2023 | 17* | 2023 |
| Multi-resolution path cnn with deep supervision for intervertebral disc localization and segmentation Y Gao, C Liu, L Zhao Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 16 | 2019 |
| Region proposal rectification towards robust instance segmentation of biological images Q Zhangli, J Yi, D Liu, X He, Z Xia, Q Chang, L Han, Y Gao, S Wen, ... International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 14 | 2022 |
| Lepard: Learning explicit part discovery for 3d articulated shape reconstruction D Liu, A Stathopoulos, Q Zhangli, Y Gao, D Metaxas Advances in Neural Information Processing Systems 36, 2024 | 10 | 2024 |
| Deep deformable models: Learning 3d shape abstractions with part consistency D Liu, L Zhao, Q Zhangli, Y Gao, T Liu, DN Metaxas arXiv preprint arXiv:2309.01035, 2023 | 4 | 2023 |
| Modality Bank: Learn multi-modality images across data centers without sharing medical data Q Chang, H Qu, Z Yan, Y Gao, L Baskaran, D Metaxas 2022 44th Annual International Conference of the IEEE Engineering in …, 2022 | 4 | 2022 |
| Deep learning framework for fully automated intervertebral disc localization and segmentation from multi-modality MR images Y Gao Computational Methods and Clinical Applications for Spine Imaging: 5th …, 2019 | 4 | 2019 |
| Aligning Human Knowledge with Visual Concepts Towards Explainable Medical Image Classification Y Gao, D Gu, M Zhou, D Metaxas arXiv preprint arXiv:2406.05596, 2024 | 3 | 2024 |
| Deep Physics-based Deformable Models for Efficient Shape Abstractions D Liu, L Zhao, Y Gao, Q Zhangli, T Liu, DN Metaxas | 1 | 2023 |
| Implicit In-context Learning Z Li, Z Xu, L Han, Y Gao, S Wen, D Liu, H Wang, DN Metaxas arXiv preprint arXiv:2405.14660, 2024 | | 2024 |
Dimitris N. MetaxasBoard of Governors and Distinguished Professor of Computer Science, Rutgers UniversityVerified email at cs.rutgers.edu
