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Ruogu Fang
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2020 – today
- 2024
- [j28]Qiaosi Tang
, Ranjala Ratnayake, Gustavo de M. Seabra
Morphological profiling for drug discovery in the era of deep learning. Briefings Bioinform. 25(4) (2024) - [j27]Tianqi Liu
Texture and motion aware perception in-loop filter for AV1. J. Vis. Commun. Image Represent. 98: 104025 (2024) - [j26]Joseph Cox, Peng Liu, Skylar E. Stolte, Yunchao Yang, Kang Liu, Kyle B. See
BrainSegFounder: Towards 3D foundation models for neuroimage segmentation. Medical Image Anal. 97: 103301 (2024) - [j25]Peng Liu
Emergence of Emotion Selectivity in Deep Neural Networks Trained to Recognize Visual Objects. PLoS Comput. Biol. 20(3): 1011943 (2024) - [j24]Chaoyue Sun
DeepDynaForecast: Phylogenetic-informed graph deep learning for epidemic transmission dynamic prediction. PLoS Comput. Biol. 20(4): 1011351 (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
Ethnic disparity in diagnosing asymptomatic bacterial vaginosis using machine learning. npj Digit. Medicine 6 (2023) - [j22]Skylar E. Stolte, Kyle Volle, Aprinda Indahlastari
DOMINO: Domain-aware loss for deep learning calibration. Softw. Impacts 15: 100478 (2023) - [c28]Hong Huang
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 T. 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
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 T. 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
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
DOMINO: Domain-Aware Model Calibration in Medical Image Segmentation. MICCAI (5) 2022: 454-463 - [i11]Skylar E. Stolte, Kyle Volle, Aprinda Indahlastari
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
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
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
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
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
Domain-invariant interpretable fundus image quality assessment. Medical Image Anal. 61: 101654 (2020) - [j15]Skylar E. Stolte
A survey on medical image analysis in diabetic retinopathy. Medical Image Anal. 64: 101742 (2020) - [c23]Yao Xiao, Keith R. Peters, W. Christopher Fox
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). 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
Deep Evolutionary Networks with Expedited Genetic Algorithms for Medical Image Denoising. Medical Image Anal. 54: 306-315 (2019) - [j13]Bin Sheng
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
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
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
Mining Big Neuron Morphological Data. Comput. Intell. Neurosci. 2018: 8234734:1-8234734:13 (2018) - [j11]Saleha Masood, Bin Sheng, Ping Li
Automatic choroid layer segmentation using normalized graph cut. IET Image Process. 12(1): 53-59 (2018) - [j10]Ling Dai
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
Neural Network Evolution Using Expedited Genetic Algorithm for Medical Image Denoising. MICCAI (1) 2018: 12-20 - [c17]Yaxin Shen, Ruogu Fang
Multi-task Fundus Image Quality Assessment via Transfer Learning and Landmarks Detection. MLMI@MICCAI 2018: 28-36 - 2017
- [j9]Ruogu Fang
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
Abdominal adipose tissues extraction using multi-scale deep neural network. Neurocomputing 229: 23-33 (2017) - [j7]Zhongyu Li, Ruogu Fang
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
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
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
Maximum inner product search for morphological retrieval of large-scale neuron data. ISBI 2016: 602-606 - [c12]Ruogu Fang
Direct estimation of permeability maps for low-dose CT perfusion. ISBI 2016: 739-742 - 2015
- [j5]Ruogu Fang
Sparsity techniques in medical imaging. Comput. Medical Imaging Graph. 46: 1 (2015) - [j4]Ruogu Fang
Tissue-specific sparse deconvolution for brain CT perfusion. Comput. Medical Imaging Graph. 46: 64-72 (2015) - [j3]Ruogu Fang
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
Leveraging coupled multi-index for scalable retrieval of mammographic masses. ISBI 2015: 276-280 - [c10]Ruogu Fang
A spatio-temporal low-rank total variation approach for denoising arterial spin labeling MRI data. ISBI 2015: 498-502 - [c9]Ruogu Fang
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
Fast Preconditioning for Accelerated Multi-contrast MRI Reconstruction. MICCAI (2) 2015: 700-707 - 2014
- [j2]Ruogu Fang
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
Tensor Total-Variation Regularized Deconvolution for Efficient Low-Dose CT Perfusion. MICCAI (1) 2014: 154-161 - 2013
- [j1]Ruogu Fang
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
Kinship classification by modeling facial feature heredity. ICIP 2013: 2983-2987 - [c5]Ruogu Fang
Tissue-Specific Sparse Deconvolution for Low-Dose CT Perfusion. MICCAI (1) 2013: 114-121 - 2012
- [c4]Ruogu Fang
Sparsity-based deconvolution of low-dose brain perfusion CT in subarachnoid hemorrhage patients. ISBI 2012: 872-875 - [c3]Ruogu Fang
Sparsity-Based Deconvolution of Low-Dose Perfusion CT Using Learned Dictionaries. MICCAI (1) 2012: 272-280 - 2011
- [c2]Ruogu Fang
Segmentation of Liver Tumor Using Efficient Global Optimal Tree Metrics Graph Cuts. Abdominal Imaging 2011: 51-59 - 2010
- [c1]Ruogu Fang
Towards computational models of kinship verification. ICIP 2010: 1577-1580
Coauthor Index
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last updated on 2024-12-02 21:27 CET by the dblp team
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