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2020 – today
- 2024
[j26]Qiaosi Tang
, Ranjala Ratnayake, Gustavo de M. Seabra, Zhe Jiang, Ruogu Fang, Lina Cui, Yousong Ding, Tamer Kahveci, Jiang Bian, Chenglong Li, Hendrik Luesch, Yanjun Li:
Morphological profiling for drug discovery in the era of deep learning. Briefings Bioinform. 25(4) (2024)- [j25]Tianqi Liu, Hong Huang, Zhijun Lei, Ruogu Fang, Dapeng Oliver Wu:
Texture and motion aware perception in-loop filter for AV1. J. Vis. Commun. Image Represent. 98: 104025 (2024) - [j24]Joseph Cox, Peng Liu, Skylar E. Stolte, Yunchao Yang, Kang Liu, Kyle B. See, Huiwen Ju, Ruogu Fang:
BrainSegFounder: Towards 3D foundation models for neuroimage segmentation. Medical Image Anal. 97: 103301 (2024) - [c30]Chaoyue Sun, Yiyang Liu, Christina Parisi, Rebecca Fisk-Hoffman, Marco Salemi, Ruogu Fang, Brandi Danforth, Mattia Prosperi, Simone Marini:
Learning on Forecasting HIV Epidemic Based on Individuals' Contact Networks. BIOSTEC (2) 2024: 103-111 - [c29]Skylar E. Stolte, Aprinda Indahlastari, Alejandro Albizu, Adam J. Woods, Ruogu Fang:
Towards tDCS Digital Twins Using Deep Learning-Based Direct Estimation of Personalized Electrical Field Maps from T1-Weighted MRI. MICCAI (2) 2024: 465-475 - [i18]Joseph Cox, Peng Liu, Skylar E. Stolte, Yunchao Yang, Kang Liu, Kyle B. See, Huiwen Ju, Ruogu Fang:
BrainFounder: Towards Brain Foundation Models for Neuroimage Analysis. CoRR abs/2406.10395 (2024) - [i17]Wasif Khan, Seowung Leem, Kyle B. See, Joshua K. Wong, Shaoting Zhang, Ruogu Fang:
A Comprehensive Survey of Foundation Models in Medicine. CoRR abs/2406.10729 (2024) - 2023
- [j23]Cameron Celeste, Dion Ming, Justin Broce, Diandra P. Ojo, Emma Drobina, Adetola F. Louis-Jacques, Juan E. Gilbert, Ruogu Fang, Ivana K. Parker:
Ethnic disparity in diagnosing asymptomatic bacterial vaginosis using machine learning. npj Digit. Medicine 6 (2023) - [j22]Skylar E. Stolte, Kyle Volle, Aprinda Indahlastari, Alejandro Albizu, Adam J. Woods, Kevin M. Brink, Matthew Hale, Ruogu Fang:
DOMINO: Domain-aware loss for deep learning calibration. Softw. Impacts 15: 100478 (2023) - [c28]Hong Huang, Lan Zhang, Chaoyue Sun, Ruogu Fang, Xiaoyong Yuan, Dapeng Wu:
Distributed Pruning Towards Tiny Neural Networks in Federated Learning. ICDCS 2023: 190-201 - [c27]Skylar E. Stolte, Kyle Volle, Aprinda Indahlastari, Alejandro Albizu, Adam J. Woods, Kevin M. Brink, Matthew Hale, Ruogu Fang:
DOMINO++: Domain-Aware Loss Regularization for Deep Learning Generalizability. MICCAI (4) 2023: 713-723 - [i16]Nooshin Yousefzadeh, Charlie T. Tran, Adolfo Ramirez-Zamora, Jinghua Chen, Ruogu Fang, My T. Thai:
LAVA: Granular Neuron-Level Explainable AI for Alzheimer's Disease Assessment from Fundus Images. CoRR abs/2302.03008 (2023) - [i15]Skylar E. Stolte, Kyle Volle, Aprinda Indahlastari, Alejandro Albizu, Adam J. Woods, Kevin M. Brink, Matthew Hale, Ruogu Fang:
DOMINO: Domain-aware Loss for Deep Learning Calibration. CoRR abs/2302.05142 (2023) - [i14]Charlie T. Tran, Kai Shen, Kevin Liu, Ruogu Fang:
Deep Learning Predicts Prevalent and Incident Parkinson's Disease From UK Biobank Fundus Imaging. CoRR abs/2302.06727 (2023) - [i13]Skylar E. Stolte, Kyle Volle, Aprinda Indahlastari, Alejandro Albizu, Adam J. Woods, Kevin M. Brink, Matthew Hale, Ruogu Fang:
DOMINO++: Domain-aware Loss Regularization for Deep Learning Generalizability. CoRR abs/2308.10453 (2023) - [i12]Qiaosi Tang, Ranjala Ratnayake, Gustavo de M. Seabra, Zhe Jiang, Ruogu Fang, Lina Cui, Yousong Ding, Tamer Kahveci, Jiang Bian, Chenglong Li, Hendrik Luesch, Yanjun Li:
Morphological Profiling for Drug Discovery in the Era of Deep Learning. CoRR abs/2312.07899 (2023) - 2022
- [j21]Peng Liu, Charlie T. Tran, Bin Kong, Ruogu Fang:
CADA: Multi-scale Collaborative Adversarial Domain Adaptation for unsupervised optic disc and cup segmentation. Neurocomputing 469: 209-220 (2022) - [j20]Zehao Yu, Xi Yang, Gianna L. Sweeting, Yinghan Ma, Skylar E. Stolte, Ruogu Fang, Yonghui Wu:
Identify diabetic retinopathy-related clinical concepts and their attributes using transformer-based natural language processing methods. BMC Medical Informatics Decis. Mak. 22-S(3): 255 (2022) - [c26]Zehao Yu, Xi Yang, Yiqing Chen, Ruogu Fang, William R. Hogan, Yan Gong, Yonghui Wu:
Identify Cancer Patients at Risk for Heart Failure using Electronic Health Record and Genetic Data. ICHI 2022: 138-142 - [c25]Skylar E. Stolte, Kyle Volle, Aprinda Indahlastari, Alejandro Albizu, Adam J. Woods, Kevin M. Brink, Matthew Hale, Ruogu Fang:
DOMINO: Domain-Aware Model Calibration in Medical Image Segmentation. MICCAI (5) 2022: 454-463 - [i11]Skylar E. Stolte, Kyle Volle, Aprinda Indahlastari, Alejandro Albizu, Adam J. Woods, Kevin M. Brink, Matthew Hale, Ruogu Fang:
DOMINO: Domain-aware Model Calibration in Medical Image Segmentation. CoRR abs/2209.06077 (2022) - [i10]Hong Huang, Lan Zhang, Chaoyue Sun, Ruogu Fang, Xiaoyong Yuan, Dapeng Wu:
FedTiny: Pruned Federated Learning Towards Specialized Tiny Models. CoRR abs/2212.01977 (2022) - 2021
- [j19]Kyle B. See, David J. Arpin, David E. Vaillancourt, Ruogu Fang, Stephen A. Coombes:
Unraveling somatotopic organization in the human brain using machine learning and adaptive supervoxel-based parcellations. NeuroImage 245: 118710 (2021) - [c24]Zehao Yu, Xi Yang, Gianna L. Sweeting, Yinghan Ma, Skylar E. Stolte, Ruogu Fang, Yonghui Wu:
Identify Diabetic Retinopathy-related Clinical Concepts Using Transformer-based Natural Language Processing Methods. ICHI 2021: 499-500 - [i9]Peng Liu, Charlie T. Tran, Bin Kong, Ruogu Fang:
CADA: Multi-scale Collaborative Adversarial Domain Adaptation for Unsupervised Optic Disc and Cup Segmentation. CoRR abs/2110.02417 (2021) - 2020
- [j18]Xi Yang, Jiang Bian, Ruogu Fang, Ragnhildur I. Bjarnadottir, William R. Hogan, Yonghui Wu:
Identifying relations of medications with adverse drug events using recurrent convolutional neural networks and gradient boosting. J. Am. Medical Informatics Assoc. 27(1): 65-72 (2020) - [j17]José Ignacio Orlando, Huazhu Fu, João Barbosa Breda, Karel van Keer, Deepti R. Bathula, Andrés Diaz-Pinto, Ruogu Fang, Pheng-Ann Heng, Jeyoung Kim, Joonho Lee, Joonseok Lee, Xiaoxiao Li, Peng Liu, Shuai Lu, Balamurali Murugesan, Valery Naranjo, Sai Samarth R. Phaye, Sharath M. Shankaranarayana, Hrvoje Bogunovic:
REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs. Medical Image Anal. 59 (2020) - [j16]Yaxin Shen, Bin Sheng, Ruogu Fang, Huating Li, Ling Dai, Skylar E. Stolte, Jing Qin, Weiping Jia, Dinggang Shen:
Domain-invariant interpretable fundus image quality assessment. Medical Image Anal. 61: 101654 (2020) - [j15]Skylar E. Stolte, Ruogu Fang:
A survey on medical image analysis in diabetic retinopathy. Medical Image Anal. 64: 101742 (2020) - [c23]Yao Xiao, Keith R. Peters, W. Christopher Fox, John H. Rees, Dhanashree A. Rajderkar, Manuel M. Arreola, Izabella Barreto, Wesley E. Bolch, Ruogu Fang:
Transfer-Gan: Multimodal Ct Image Super-Resolution Via Transfer Generative Adversarial Networks. ISBI 2020: 195-198 - [c22]Yao Xiao, Ruogu Fang:
Transfer generative adversarial network for multimodal CT image super-resolution (Conference Presentation). Medical Imaging: Image Processing 2020: 1131306 - [i8]Peng Liu, Ruogu Fang:
Regression and Learning with Pixel-wise Attention for Retinal Fundus Glaucoma Segmentation and Detection. CoRR abs/2001.01815 (2020)
2010 – 2019
- 2019
- [j14]Peng Liu, Mohammad D. El Basha, Yangjunyi Li, Yao Xiao, Pina C. Sanelli, Ruogu Fang:
Deep Evolutionary Networks with Expedited Genetic Algorithms for Medical Image Denoising. Medical Image Anal. 54: 306-315 (2019) - [j13]Bin Sheng, Ping Li, Shuangjia Mo, Huating Li, Xuhong Hou, Qiang Wu, Jing Qin, Ruogu Fang, David Dagan Feng:
Retinal Vessel Segmentation Using Minimum Spanning Superpixel Tree Detector. IEEE Trans. Cybern. 49(7): 2707-2719 (2019) - [c21]Siyuan Pan, Xuhong Hou, Huating Li, Bin Sheng, Ruogu Fang, Yuxin Xue, Weiping Jia, Jing Qin:
Abdominal Adipose Tissue Segmentation in MRI with Double Loss Function Collaborative Learning. MICCAI (6) 2019: 41-49 - [c20]Peng Liu, Bin Kong, Zhongyu Li, Shaoting Zhang, Ruogu Fang:
CFEA: Collaborative Feature Ensembling Adaptation for Domain Adaptation in Unsupervised Optic Disc and Cup Segmentation. MICCAI (5) 2019: 521-529 - [p1]Yao Xiao, Skylar E. Stolte, Peng Liu, Yun Liang, Pina C. Sanelli, Ajay Gupta, Jana Ivanidze, Ruogu Fang:
Deep Spatial-Temporal Convolutional Neural Networks for Medical Image Restoration. Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics 2019: 261-275 - [i7]José Ignacio Orlando, Huazhu Fu, João Barbosa Breda, Karel van Keer, Deepti R. Bathula, Andrés Diaz-Pinto, Ruogu Fang, Pheng-Ann Heng, Jeyoung Kim, Joonho Lee, Joonseok Lee, Xiaoxiao Li, Peng Liu, Shuai Lu, Balamurali Murugesan, Valery Naranjo, Sai Samarth R. Phaye, Sharath M. Shankaranarayana, Apoorva Sikka, Jaemin Son, Anton van den Hengel, Shujun Wang, Junyan Wu, Zifeng Wu, Guanghui Xu, Yong-Li Xu, Pengshuai Yin, Fei Li, Xiulan Zhang, Yanwu Xu, Hrvoje Bogunovic:
REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs. CoRR abs/1910.03667 (2019) - [i6]Peng Liu, Bin Kong, Zhongyu Li, Shaoting Zhang, Ruogu Fang:
CFEA: Collaborative Feature Ensembling Adaptation for Domain Adaptation in Unsupervised Optic Disc and Cup Segmentation. CoRR abs/1910.07638 (2019) - [i5]Peng Liu, Ruogu Fang:
SDCNet: Smoothed Dense-Convolution Network for Restoring Low-Dose Cerebral CT Perfusion. CoRR abs/1910.08364 (2019) - [i4]Peng Liu, Xiaoxiao Zhou, Junyi Yang, Mohammad D. El Basha, Ruogu Fang:
Image Restoration Using Deep Regulated Convolutional Networks. CoRR abs/1910.08853 (2019) - [i3]Peng Liu, Xiaoxiao Zhou, Junyiyang Li, Mohammad D. El Basha, Ruogu Fang:
KRNET: Image Denoising with Kernel Regulation Network. CoRR abs/1910.08867 (2019) - 2018
- [j12]Maryamossadat Aghili, Ruogu Fang:
Mining Big Neuron Morphological Data. Comput. Intell. Neurosci. 2018: 8234734:1-8234734:13 (2018) - [j11]Saleha Masood, Bin Sheng, Ping Li, Ruimin Shen, Ruogu Fang, Qiang Wu:
Automatic choroid layer segmentation using normalized graph cut. IET Image Process. 12(1): 53-59 (2018) - [j10]Ling Dai, Ruogu Fang, Huating Li, Xuhong Hou, Bin Sheng, Qiang Wu, Weiping Jia:
Clinical Report Guided Retinal Microaneurysm Detection With Multi-Sieving Deep Learning. IEEE Trans. Medical Imaging 37(5): 1149-1161 (2018) - [c19]Peng Liu, Ruogu Fang:
SDCNet: Smoothed dense-convolution network for restoring low-dose cerebral CT perfusion. ISBI 2018: 349-352 - [c18]Peng Liu, Yangjunyi Li, Mohammad D. El Basha, Ruogu Fang:
Neural Network Evolution Using Expedited Genetic Algorithm for Medical Image Denoising. MICCAI (1) 2018: 12-20 - [c17]Yaxin Shen, Ruogu Fang, Bin Sheng, Ling Dai, Huating Li, Jing Qin, Qiang Wu, Weiping Jia:
Multi-task Fundus Image Quality Assessment via Transfer Learning and Landmarks Detection. MLMI@MICCAI 2018: 28-36 - 2017
- [j9]Ruogu Fang, Ajay Gupta, Junzhou Huang, Pina C. Sanelli:
TENDER: Tensor non-local deconvolution enabled radiation reduction in CT perfusion. Neurocomputing 229: 13-22 (2017) - [j8]Fei Jiang, Huating Li, Xuhong Hou, Bin Sheng, Ruimin Shen, Xiao-Yang Liu, Weiping Jia, Ping Li, Ruogu Fang:
Abdominal adipose tissues extraction using multi-scale deep neural network. Neurocomputing 229: 23-33 (2017) - [j7]Zhongyu Li, Ruogu Fang, Fumin Shen, Amin Katouzian, Shaoting Zhang:
Indexing and mining large-scale neuron databases using maximum inner product search. Pattern Recognit. 63: 680-688 (2017) - [c16]Yao Xiao, Ruogu Fang:
RFMiner: Risk Factors Discovery and Mining for Preventive Cardiovascular Health. CHASE 2017: 278-279 - [c15]Yao Xiao, Ajay Gupta, Pina C. Sanelli, Ruogu Fang:
STAR: Spatio-Temporal Architecture for Super-Resolution in Low-Dose CT Perfusion. MLMI@MICCAI 2017: 97-105 - [c14]Ling Dai, Bin Sheng, Qiang Wu, Huating Li, Xuhong Hou, Weiping Jia, Ruogu Fang:
Retinal Microaneurysm Detection Using Clinical Report Guided Multi-sieving CNN. MICCAI (3) 2017: 525-532 - [i2]Peng Liu, Ruogu Fang:
Wide Inference Network for Image Denoising. CoRR abs/1707.05414 (2017) - [i1]Peng Liu, Ruogu Fang:
Learning Pixel-Distribution Prior with Wider Convolution for Image Denoising. CoRR abs/1707.09135 (2017) - 2016
- [j6]Ruogu Fang, Samira Pouyanfar, Yimin Yang, Shu-Ching Chen, S. S. Iyengar:
Computational Health Informatics in the Big Data Age: A Survey. ACM Comput. Surv. 49(1): 12:1-12:36 (2016) - [c13]Zhongyu Li, Fumin Shen, Ruogu Fang, Sailesh Conjeti, Amin Katouzian, Shaoting Zhang:
Maximum inner product search for morphological retrieval of large-scale neuron data. ISBI 2016: 602-606 - [c12]Ruogu Fang, Ajay Gupta, Pina C. Sanelli:
Direct estimation of permeability maps for low-dose CT perfusion. ISBI 2016: 739-742 - 2015
- [j5]Ruogu Fang, Tsuhan Chen, Dimitris N. Metaxas, Pina C. Sanelli, Shaoting Zhang:
Sparsity techniques in medical imaging. Comput. Medical Imaging Graph. 46: 1 (2015) - [j4]Ruogu Fang, Haodi Jiang, Junzhou Huang:
Tissue-specific sparse deconvolution for brain CT perfusion. Comput. Medical Imaging Graph. 46: 64-72 (2015) - [j3]Ruogu Fang, Shaoting Zhang, Tsuhan Chen, Pina C. Sanelli:
Robust Low-Dose CT Perfusion Deconvolution via Tensor Total-Variation Regularization. IEEE Trans. Medical Imaging 34(7): 1533-1548 (2015) - [c11]Menglin Jiang, Shaoting Zhang, Ruogu Fang, Dimitris N. Metaxas:
Leveraging coupled multi-index for scalable retrieval of mammographic masses. ISBI 2015: 276-280 - [c10]Ruogu Fang, Junzhou Huang, Wen-Ming Luh:
A spatio-temporal low-rank total variation approach for denoising arterial spin labeling MRI data. ISBI 2015: 498-502 - [c9]Ruogu Fang, Ming Ni, Junzhou Huang, Qianmu Li, Tao Li:
Efficient 4D Non-local Tensor Total-Variation for Low-Dose CT Perfusion Deconvolution. MCV@MICCAI 2015: 168-179 - [c8]Ruoyu Li, Yeqing Li, Ruogu Fang, Shaoting Zhang, Hao Pan, Junzhou Huang:
Fast Preconditioning for Accelerated Multi-contrast MRI Reconstruction. MICCAI (2) 2015: 700-707 - 2014
- [j2]Ruogu Fang, Kolbeinn Karlsson, Tsuhan Chen, Pina C. Sanelli:
Improving low-dose blood-brain barrier permeability quantification using sparse high-dose induced prior for Patlak model. Medical Image Anal. 18(6): 866-880 (2014) - [c7]Ruogu Fang, Pina C. Sanelli, Shaoting Zhang, Tsuhan Chen:
Tensor Total-Variation Regularized Deconvolution for Efficient Low-Dose CT Perfusion. MICCAI (1) 2014: 154-161 - 2013
- [j1]Ruogu Fang, Tsuhan Chen, Pina C. Sanelli:
Towards robust deconvolution of low-dose perfusion CT: Sparse perfusion deconvolution using online dictionary learning. Medical Image Anal. 17(4): 417-428 (2013) - [c6]Ruogu Fang, Andrew C. Gallagher, Tsuhan Chen, Alexander C. Loui:
Kinship classification by modeling facial feature heredity. ICIP 2013: 2983-2987 - [c5]Ruogu Fang, Tsuhan Chen, Pina C. Sanelli:
Tissue-Specific Sparse Deconvolution for Low-Dose CT Perfusion. MICCAI (1) 2013: 114-121 - 2012
- [c4]Ruogu Fang, Tsuhan Chen, Pina C. Sanelli:
Sparsity-based deconvolution of low-dose brain perfusion CT in subarachnoid hemorrhage patients. ISBI 2012: 872-875 - [c3]Ruogu Fang, Tsuhan Chen, Pina C. Sanelli:
Sparsity-Based Deconvolution of Low-Dose Perfusion CT Using Learned Dictionaries. MICCAI (1) 2012: 272-280 - 2011
- [c2]Ruogu Fang, Ramin Zabih, Ashish Raj, Tsuhan Chen:
Segmentation of Liver Tumor Using Efficient Global Optimal Tree Metrics Graph Cuts. Abdominal Imaging 2011: 51-59 - 2010
- [c1]Ruogu Fang, Kevin D. Tang, Noah Snavely, Tsuhan Chen:
Towards computational models of kinship verification. ICIP 2010: 1577-1580
Coauthor Index
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