| Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs JI Orlando, H Fu, JB Breda, K Van Keer, DR Bathula, A Diaz-Pinto, ... Medical image analysis 59, 101570, 2020 | 692 | 2020 |
| Towards computational models of kinship verification R Fang, KD Tang, N Snavely, T Chen 2010 IEEE International conference on image processing, 1577-1580, 2010 | 357 | 2010 |
| Idrid: Diabetic retinopathy–segmentation and grading challenge P Porwal, S Pachade, M Kokare, G Deshmukh, J Son, W Bae, L Liu, ... Medical image analysis 59, 101561, 2020 | 314 | 2020 |
| Computational health informatics in the big data age: a survey R Fang, S Pouyanfar, Y Yang, SC Chen, SS Iyengar ACM Computing Surveys (CSUR) 49 (1), 1-36, 2016 | 301 | 2016 |
| Clinical report guided retinal microaneurysm detection with multi-sieving deep learning L Dai, R Fang, H Li, X Hou, B Sheng, Q Wu, W Jia IEEE transactions on medical imaging 37 (5), 1149-1161, 2018 | 166 | 2018 |
| Kinship classification by modeling facial feature heredity R Fang, AC Gallagher, T Chen, A Loui 2013 IEEE international conference on image processing, 2983-2987, 2013 | 136 | 2013 |
| A survey on medical image analysis in diabetic retinopathy S Stolte, R Fang Medical image analysis 64, 101742, 2020 | 126 | 2020 |
| Automatic choroid layer segmentation from optical coherence tomography images using deep learning S Masood, R Fang, P Li, H Li, B Sheng, A Mathavan, X Wang, P Yang, ... Scientific reports 9 (1), 3058, 2019 | 106 | 2019 |
| Development and validation of the automated imaging differentiation in parkinsonism (AID-P): a multicentre machine learning study DB Archer, JT Bricker, WT Chu, RG Burciu, JL McCracken, S Lai, ... The Lancet Digital Health 1 (5), e222-e231, 2019 | 102 | 2019 |
| Modular machine learning for Alzheimer's disease classification from retinal vasculature J Tian, G Smith, H Guo, B Liu, Z Pan, Z Wang, S Xiong, R Fang Scientific Reports 11 (1), 238, 2021 | 98 | 2021 |
| Deep evolutionary networks with expedited genetic algorithms for medical image denoising P Liu, MD El Basha, Y Li, Y Xiao, PC Sanelli, R Fang Medical image analysis 54, 306-315, 2019 | 97 | 2019 |
| Domain-invariant interpretable fundus image quality assessment Y Shen, B Sheng, R Fang, H Li, L Dai, S Stolte, J Qin, W Jia, D Shen Medical image analysis 61, 101654, 2020 | 93 | 2020 |
| Retinal vessel segmentation using minimum spanning superpixel tree detector B Sheng, P Li, S Mo, H Li, X Hou, Q Wu, J Qin, R Fang, DD Feng IEEE transactions on cybernetics 49 (7), 2707-2719, 2018 | 78 | 2018 |
| Machine learning and individual variability in electric field characteristics predict tDCS treatment response A Albizu, R Fang, A Indahlastari, A O’Shea, SE Stolte, KB See, ... Brain stimulation 13 (6), 1753-1764, 2020 | 75 | 2020 |
| Identifying relations of medications with adverse drug events using recurrent convolutional neural networks and gradient boosting X Yang, J Bian, R Fang, RI Bjarnadottir, WR Hogan, Y Wu Journal of the American Medical Informatics Association 27 (1), 65-72, 2020 | 74 | 2020 |
| Towards robust deconvolution of low-dose perfusion CT: Sparse perfusion deconvolution using online dictionary learning R Fang, T Chen, PC Sanelli Medical Image Analysis, 2013 | 69 | 2013 |
| Robust low-dose CT perfusion deconvolution via tensor total-variation regularization R Fang, S Zhang, T Chen, PC Sanelli IEEE transactions on medical imaging 34 (7), 1533-1548, 2015 | 67 | 2015 |
| Low-rise gable roof buildings pressure prediction using deep neural networks J Tian, KR Gurley, MT Diaz, PL Fernández-Cabán, FJ Masters, R Fang Journal of Wind Engineering and Industrial Aerodynamics 196, 104026, 2020 | 57 | 2020 |
| Machine learning for physics-informed generation of dispersed multiphase flow using generative adversarial networks B Siddani, S Balachandar, WC Moore, Y Yang, R Fang Theoretical and Computational Fluid Dynamics 35, 807-830, 2021 | 51 | 2021 |
| Big data in multimodal medical imaging A El-Baz, JS Suri CRC Press, 2019 | 48 | 2019 |
Tsuhan ChenNational University of Singaporeبريد إلكتروني تم التحقق منه على nus.edu.sg