Ruogu Fang
Cited by
Cited by
Towards computational models of kinship verification
R Fang, KD Tang, N Snavely, T Chen
2010 IEEE International conference on image processing, 1577-1580, 2010
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
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, R Fang, ...
Medical image analysis 59, 101570, 2020
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
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
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
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
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
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
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
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), 1-18, 2019
A survey on medical image analysis in diabetic retinopathy
S Stolte, R Fang
Medical image analysis 64, 101742, 2020
Wide inference network for image denoising via learning pixel-distribution prior
P Liu, R Fang
arXiv preprint arXiv:1707.05414, 2017
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
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
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
Learning pixel-distribution prior with wider convolution for image denoising
P Liu, R Fang
arXiv preprint arXiv:1707.09135, 2017
Abdominal adipose tissues extraction using multi-scale deep neural network
F Jiang, H Li, X Hou, B Sheng, R Shen, XY Liu, W Jia, P Li, R Fang
Neurocomputing 229, 23-33, 2017
Improving low-dose blood–brain barrier permeability quantification using sparse high-dose induced prior for patlak model
R Fang, K Karlsson, T Chen, PC Sanelli
Medical image analysis 18 (6), 866-880, 2014
Retinal microaneurysm detection using clinical report guided multi-sieving CNN
L Dai, B Sheng, Q Wu, H Li, X Hou, W Jia, R Fang
International Conference on Medical Image Computing and Computer-Assisted …, 2017
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