| Three-dimensional segmentation of fluid-associated abnormalities in retinal OCT: probability constrained graph-search-graph-cut X Chen, M Niemeijer, L Zhang, K Lee, MD Abràmoff, M Sonka IEEE transactions on medical imaging 31 (8), 1521-1531, 2012 | 212 | 2012 |
| Automated segmentation of the choroid from clinical SD-OCT L Zhang, K Lee, M Niemeijer, RF Mullins, M Sonka, MD Abramoff Investigative ophthalmology & visual science 53 (12), 7510-7519, 2012 | 156 | 2012 |
| Multi-level domain adaptive learning for cross-domain detection R Xie, F Yu, J Wang, Y Wang, L Zhang Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 109 | 2019 |
| Three-dimensional automated choroidal volume assessment on standard spectral-domain optical coherence tomography and correlation with the level of diabetic macular edema BS Gerendas, SM Waldstein, C Simader, G Deak, B Hajnajeeb, L Zhang, ... American journal of ophthalmology 158 (5), 1039-1048. e1, 2014 | 92 | 2014 |
| Stratified sampling voxel classification for segmentation of intraretinal and subretinal fluid in longitudinal clinical OCT data X Xu, K Lee, L Zhang, M Sonka, MD Abramoff IEEE transactions on medical imaging 34 (7), 1616-1623, 2015 | 91 | 2015 |
| Validity of automated choroidal segmentation in SS-OCT and SD-OCT L Zhang, GHS Buitendijk, K Lee, M Sonka, H Springelkamp, A Hofman, ... Investigative ophthalmology & visual science 56 (5), 3202-3211, 2015 | 85 | 2015 |
| Skin disease diagnosis with deep learning: a review H Li, Y Pan, J Zhao, L Zhang Neurocomputing 464, 364-393, 2021 | 83 | 2021 |
| Dast: Unsupervised domain adaptation in semantic segmentation based on discriminator attention and self-training F Yu, M Zhang, H Dong, S Hu, B Dong, L Zhang Proceedings of the AAAI Conference on Artificial Intelligence 35 (12), 10754 …, 2021 | 69 | 2021 |
| Predicting response to immunotherapy in gastric cancer via multi-dimensional analyses of the tumour immune microenvironment Y Chen, K Jia, Y Sun, C Zhang, Y Li, L Zhang, Z Chen, J Zhang, Y Hu, ... Nature Communications 13 (1), 4851, 2022 | 57 | 2022 |
| CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation R Dorent, A Kujawa, M Ivory, S Bakas, N Rieke, S Joutard, B Glocker, ... Medical Image Analysis 83, 102628, 2023 | 51 | 2023 |
| Quantification of external limiting membrane disruption caused by diabetic macular edema from SD-OCT X Chen, L Zhang, EH Sohn, K Lee, M Niemeijer, J Chen, M Sonka, ... Investigative ophthalmology & visual science 53 (13), 8042-8048, 2012 | 48 | 2012 |
| Automated segmentation of cervical nuclei in pap smear images using deformable multi-path ensemble model J Zhao, Q Li, X Li, H Li, L Zhang 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019 …, 2019 | 43 | 2019 |
| Choroidal thickness maps from spectral domain and swept source optical coherence tomography: algorithmic versus ground truth annotation AM Philip, BS Gerendas, L Zhang, H Faatz, D Podkowinski, H Bogunovic, ... British Journal of Ophthalmology 100 (10), 1372-1376, 2016 | 42 | 2016 |
| BEFD: Boundary enhancement and feature denoising for vessel segmentation M Zhang, F Yu, J Zhao, L Zhang, Q Li Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 41 | 2020 |
| Spatial correspondence between intraretinal fluid, subretinal fluid, and pigment epithelial detachment in neovascular age-related macular degeneration S Klimscha, SM Waldstein, T Schlegl, H Bogunović, A Sadeghipour, ... Investigative ophthalmology & visual science 58 (10), 4039-4048, 2017 | 36 | 2017 |
| Comparison of Retinal and Choriocapillaris Thicknesses Following Sitting to Supine Transition in Healthy Individuals and Patients With Age-Related Macular Degeneration DRP Almeida, L Zhang, EK Chin, RF Mullins, M Kucukevcilioglu, ... JAMA ophthalmology 133 (3), 297-303, 2015 | 36 | 2015 |
| Annotation-free cardiac vessel segmentation via knowledge transfer from retinal images F Yu, J Zhao, Y Gong, Z Wang, Y Li, F Yang, B Dong, Q Li, L Zhang Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 35 | 2019 |
| PGU-net+: progressive growing of U-net+ for automated cervical nuclei segmentation J Zhao, L Dai, M Zhang, F Yu, M Li, H Li, W Wang, L Zhang Multiscale Multimodal Medical Imaging: First International Workshop, MMMI …, 2020 | 33 | 2020 |
| Deep learning combined with radiomics may optimize the prediction in differentiating high-grade lung adenocarcinomas in ground glass opacity lesions on CT scans X Wang, L Zhang, X Yang, L Tang, J Zhao, G Chen, X Li, S Yan, S Li, ... European journal of radiology 129, 109150, 2020 | 31 | 2020 |
| Optimal retinal cyst segmentation from OCT images I Oguz, L Zhang, MD Abràmoff, M Sonka Medical Imaging 2016: Image Processing 9784, 375-381, 2016 | 30 | 2016 |
Michael D. AbramoffProfessor of Ophthalmology and Visual Sciences, Electrical and Computer Engineering and Biomedical EngineeringBestätigte E-Mail-Adresse bei uiowa.edu
