| DeepAtlas: Joint semi-supervised learning of image registration and segmentation Z Xu, M Niethammer International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 105 | 2019 |
| Networks for joint affine and non-parametric image registration Z Shen, X Han, Z Xu, M Niethammer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 85 | 2019 |
| Robust and Generalizable Visual Representation Learning via Random Convolutions Z Xu, D Liu, J Yang, C Raffel, M Niethammer International Conference on Learning Representations (ICLR), 2021 | 80 | 2021 |
| SLIC superpixels for efficient graph-based dimensionality reduction of hyperspectral imagery X Zhang, SE Chew, Z Xu, ND Cahill Algorithms and technologies for multispectral, hyperspectral, and …, 2015 | 66 | 2015 |
| Towards fully mobile 3D face, body, and environment capture using only head-worn cameras YW Cha, T Price, Z Wei, X Lu, N Rewkowski, R Chabra, Z Qin, H Kim, ... IEEE transactions on visualization and computer graphics 24 (11), 2993-3004, 2018 | 28 | 2018 |
| A deep network for joint registration and reconstruction of images with pathologies X Han, Z Shen, Z Xu, S Bakas, H Akbari, M Bilello, C Davatzikos, ... Machine Learning in Medical Imaging: 11th International Workshop, MLMI 2020 …, 2020 | 10 | 2020 |
| Anatomical data augmentation via fluid-based image registration Z Shen, Z Xu, S Olut, M Niethammer Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 10 | 2020 |
| Adversarial data augmentation via deformation statistics S Olut, Z Shen, Z Xu, S Gerber, M Niethammer Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 6 | 2020 |
| Contextual additive networks to efficiently boost 3D image segmentations Z Xu, Z Shen, M Niethammer Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2018 | 6 | 2018 |
| iSegFormer: Interactive Segmentation via Transformers with Application to 3D Knee MR Images Q Liu, Z Xu, Y Jiao, M Niethammer Medical Image Computing and Computer Assisted Intervention–MICCAI 2022: 25th …, 2022 | 5 | 2022 |
| DADP: dynamic abnormality detection and progression for longitudinal knee magnetic resonance images from the osteoarthritis initiative C Huang, Z Xu, Z Shen, T Luo, T Li, D Nissman, A Nelson, Y Golightly, ... Medical image analysis 77, 102343, 2022 | 3 | 2022 |
| Accurate and practical method for characterizing Laguerre–Gaussian modes Z Xu, T Zhu, D Cheng, J Long, Z Huang, R Liu, P Zhang, H Gao, F Li Applied Optics 53 (8), 1644-1647, 2014 | 3 | 2014 |
| SimpleClick: Interactive Image Segmentation with Simple Vision Transformers Q Liu, Z Xu, G Bertasius, M Niethammer arXiv preprint arXiv:2210.11006, 2022 | 2 | 2022 |
| Compositional Generalization in Unsupervised Compositional Representation Learning: A Study on Disentanglement and Emergent Language Z Xu, M Niethammer, C Raffel arXiv preprint arXiv:2210.00482, 2022 | 2 | 2022 |
| 3d subject-atlas image registration for micro-computed tomography based characterization of drug delivery in the murine cochlea Z Xu Rochester Institute of Technology, 2016 | 1 | 2016 |
| Patterns of variation among baseline femoral and tibial cartilage thickness and clinical features: Data from the osteoarthritis initiative TH Keefe, MC Minnig, L Arbeeva, M Niethammer, Z Xu, Z Shen, B Chen, ... Osteoarthritis and Cartilage Open 5 (1), 100334, 2023 | | 2023 |
| Improving Dense Contrastive Learning with Dense Negative Pairs B Iskender, Z Xu, S Kornblith, E Chu, M Khademi arXiv preprint arXiv:2210.05063, 2022 | | 2022 |
| Common patterns of variation between femoral and tibial cartilage maps and baseline features from the osteoarthritis initiative T Keefe, L Arbeeva, M Niethammer, Z Xu, Z Shen, D Nissman, ... Osteoarthritis and Cartilage 29, S215-S216, 2021 | | 2021 |
Marc NiethammerProfessor of Computer Science, UNC Chapel HillVerified email at cs.unc.edu
