| Multiple surface segmentation using convolution neural nets: application to retinal layer segmentation in OCT images A Shah, L Zhou, MD Abrámoff, X Wu Biomedical optics express 9 (9), 4509-4526, 2018 | 119 | 2018 |
| 3D fully convolutional networks for co-segmentation of tumors on PET-CT images Z Zhong, Y Kim, L Zhou, K Plichta, B Allen, J Buatti, X Wu 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 113 | 2018 |
| Simultaneous cosegmentation of tumors in PET‐CT images using deep fully convolutional networks Z Zhong, Y Kim, K Plichta, BG Allen, L Zhou, J Buatti, X Wu Medical physics 46 (2), 619-633, 2019 | 91 | 2019 |
| Unsupervised anomaly localization using VAE and beta-VAE L Zhou, W Deng, X Wu arXiv preprint arXiv:2005.10686, 2020 | 17 | 2020 |
| Globally optimal OCT surface segmentation using a constrained IPM optimization H Xie, Z Pan, L Zhou, FA Zaman, DZ Chen, JB Jonas, W Xu, YX Wang, ... Optics Express 30 (2), 2453-2471, 2022 | 14 | 2022 |
| Artificial intelligence enhanced two-dimensional nanoscale nuclear magnetic resonance spectroscopy X Kong, L Zhou, Z Li, Z Yang, B Qiu, X Wu, F Shi, J Du NPJ quantum information 6 (1), 79, 2020 | 12 | 2020 |
| Robust Image Segmentation Quality Assessment L Zhou, W Deng, X Wu Medical Imaging with Deep Learning 2020, 2020 | 12 | 2020 |
| Two-dimensional nanoscale nuclear magnetic resonance spectroscopy enhanced by artificial intelligence J Yang, Z., Kong, X., Li, Z., Zhou, L., Yang, K., Yu, P., Wang, P., Wang, Y ... arXiv preprint arXiv:1902.05676, 2019 | 11* | 2019 |
| Trust but Verify: An Information-Theoretic Explanation for the Adversarial Fragility of Machine Learning Systems, and a General Defense against Adversarial Attacks J Yi, H Xie, L Zhou, X Wu, W Xu, R Mudumbai arXiv preprint arXiv: 1905.11381, 2019 | 9 | 2019 |
| Improving tumor co-segmentation on PET-CT images with 3D co-matting Z Zhong, Y Kim, L Zhou, K Plichta, B Allen, J Buatti, X Wu 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 8 | 2018 |
| Globally Optimal Segmentation of Mutually Interacting Surfaces using Deep Learning H Xie, Z Pan, L Zhou, FA Zaman, D Chen, JB Jonas, Y Wang, X Wu arXiv preprint arXiv:2007.01259, 2020 | 7 | 2020 |
| Model-Based Deep Learning for Globally Optimal Surface Segmentation X Wu, L Zhou, JM Buatti, H Xie US Patent App. 17/365,572, 2022 | 4 | 2022 |
| Deep Neural Networks for Surface Segmentation Meet Conditional Random Fields L Zhou, Z Zhong, A Shah, B Qiu, J Buatti, X Wu arXiv preprint arXiv:1906.04714, 2019 | 4 | 2019 |
| Efficient EMS decoding for non-binary LDPC codes L Zhou, J Sha, Z Wang 2012 International SoC Design Conference (ISOCC), 339-342, 2012 | 4 | 2012 |
| Globally Optimal Surface Segmentation using Deep Learning with Learnable Smoothness Priors L Zhou, X Wu arXiv preprint arXiv:2007.01217, 2020 | 2 | 2020 |
| 3-D Surface Segmentation Meets Conditional Random Fields L Zhou, Z Zhong, A Shah, X Wu arXiv preprint arXiv:1906.04714, 2019 | 2 | 2019 |
| Efficient symbol reliability based decoding for QCNB-LDPC codes L Zhou, J Sha, Y Chen, C Zhang, Z Wang 2014 IEEE International Symposium on Circuits and Systems (ISCAS), 405-408, 2014 | 2 | 2014 |
| Model-Informed Deep Learning for Surface Segmentation in Medical Imaging X Wu, L Zhou, F Zaman, B Qiu, JM Buatti International Conference on Information Processing in Medical Imaging, 822-834, 2023 | 1 | 2023 |
| Globally Optimal Surface Segmentation for Medical Images Using Deep Learning: Algorithms, Robustness and Applications L Zhou The University of Iowa, 2020 | 1 | 2020 |
| Robust Image Segmentation Quality Assessment without Ground Truth L Zhou, W Deng, X Wu arXiv preprint arXiv:1903.08773, short version accepted to MIDL2020, 2019 | | 2019 |
Xiaodong WuUniversity of Iowa在 uiowa.edu 的电子邮件经过验证
