| A deep learning algorithm to detect chronic kidney disease from retinal photographs in community-based populations C Sabanayagam, D Xu, DSW Ting, S Nusinovici, R Banu, H Hamzah, ... The Lancet Digital Health 2 (6), e295-e302, 2020 | 179 | 2020 |
| A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre CY Cheung, D Xu, CY Cheng, C Sabanayagam, YC Tham, M Yu, TH Rim, ... Nature biomedical engineering 5 (6), 498-508, 2021 | 177 | 2021 |
| Feature isolation for hypothesis testing in retinal imaging: an ischemic stroke prediction case study G Lim, ZW Lim, D Xu, DSW Ting, TY Wong, ML Lee, W Hsu Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 9510-9515, 2019 | 30 | 2019 |
| Deep-learning retinal vessel calibre measurements and risk of cognitive decline and dementia CY Cheung, WLE Wong, S Hilal, CN Kan, B Gyanwali, YC Tham, ... Brain Communications 4 (4), fcac212, 2022 | 19 | 2022 |
| FD: A feature difference based image clutter metric for targeting performance D Xu, Z Shi Infrared Physics & Technology 55 (6), 499-504, 2012 | 15 | 2012 |
| DSIM: A dissimilarity-based image clutter metric for targeting performance D Xu, Z Shi IEEE transactions on image processing 22 (10), 4108-4122, 2013 | 13 | 2013 |
| A structural difference based image clutter metric with brain cognitive model constraints D Xu, Z Shi, H Luo Infrared Physics & Technology 57, 28-35, 2013 | 10 | 2013 |
| A line mapping based automatic registration algorithm of infrared and visible images R Ai, Z Shi, D Xu, C Zhang International Symposium on Photoelectronic Detection and Imaging 2013 …, 2013 | 8 | 2013 |
| Risk of normal tension glaucoma progression from automated baseline retinal-vessel caliber analysis: A prospective cohort study TPH Lin, HYH Hui, A Ling, PP Chan, R Shen, MOM Wong, NCY Chan, ... American Journal of Ophthalmology 247, 111-120, 2023 | 7 | 2023 |
| Artificial intelligence deep learning system for predicting chronic kidney disease from retinal images TY Wong, D Xu, D Ting, S Nusinovici, C Cheung, TE Shyong, CY Cheng, ... Investigative Ophthalmology & Visual Science 60 (9), 1468-1468, 2019 | 7 | 2019 |
| Propagation mechanism for deep and wide neural networks D Xu, ML Lee, W Hsu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 6 | 2019 |
| Artificial Intelligence using Deep Learning in classifying side of the eyes and width of field for retinal fundus photographs V Bellemo, MYT Yip, Y Xie, XQ Lee, QD Nguyen, H Hamzah, J Ho, G Lim, ... Computer Vision–ACCV 2018 Workshops: 14th Asian Conference on Computer …, 2019 | 6 | 2019 |
| Patch-level regularizer for convolutional neural network D Xu, ML Lee, W Hsu 2019 IEEE International Conference on Image Processing (ICIP), 3232-3236, 2019 | 3 | 2019 |
| Image structural difference clutter metric based on human visual properties X Dejiang, S Zelin, L Haibo 红外与激光工程 42 (6), 1635-1641, 2013 | 3 | 2013 |
| Classification with dynamic data augmentation D Xu, ML Lee, W Hsu 2021 IEEE 33rd International Conference on Tools with Artificial …, 2021 | 2 | 2021 |
| A differential-based approach for vessel type classification in retinal images D Xu, G Lim, ML Lee, W Hsu 2018 25th IEEE International Conference on Image Processing (ICIP), 2790-2794, 2018 | 2 | 2018 |
| Influence of secondhand smoke exposure on the retinal vasculature of children in Hong Kong CY Cheung, XJ Zhang, HN Chan, Y Zhang, VL Yuen, W Hsu, ML Lee, ... Communications Medicine 3 (1), 155, 2023 | 1 | 2023 |
| Association between deep learning measured retinal vessel calibre and incident myocardial infarction in a retrospective cohort from the UK Biobank YL Wong, M Yu, C Chong, D Yang, D Xu, ML Lee, W Hsu, TY Wong, ... BMJ open 14 (3), e079311, 2024 | | 2024 |
| A field transition particle filter tracking algorithm D Xu, Z Shi, X Yu, Q Ding, H Luo International Symposium on Photoelectronic Detection and Imaging 2011 …, 2011 | | 2011 |
