R. Fang

发表

Deep Evolutionary Networks with Expedited Genetic Algorithms for Medical Image Denoising

Peng Liu, Yao Xiao, Pina C. Sanelli, 2019, Medical Image Anal..

Physiological wound assessment from coregistered and segmented tissue hemoglobin maps.

A. Godavarty, R. Fang, E. Robledo, 2020, Journal of the Optical Society of America. A, Optics, image science, and vision.

Modular machine learning for Alzheimer's disease classification from retinal vasculature

Glenn Smith, R. Fang, Jianqiao Tian, 2021, Scientific reports.

Automatic Choroid Layer Segmentation : A Slicing Approach

P. Li, R. Shen, Qiang Wu, 2017 .

Wound size measurement of lower extremity ulcers using segmentation algorithms

Anuradha Godavarty, Ruogu Fang, Elizabeth Solis, 2016, SPIE BiOS.

Joint image edge reconstruction and its application in multi-contrast MRI

Yunmei Chen, X. Ye, R. Fang, 2017, 1712.02000.

PIMA-CT: Physical Model-Aware Cyclic Simulation and Denoising for Ultra-Low-Dose CT Restoration

Peng Liu, Zhongyu Li, James Nguyen, 2022, Frontiers in Radiology.

Clinical Report Guided Retinal Microaneurysm Detection With Multi-Sieving Deep Learning

Bin Sheng, Ruogu Fang, Huating Li, 2018, IEEE Transactions on Medical Imaging.

Correction to: Retinal Microaneurysm Detection Using Clinical Report Guided Multi-Sieving CNN

Qiang Wu, Bin Sheng, Ruogu Fang, 2017, Medical Image Computing and Computer Assisted Intervention − MICCAI 2017.

Development and Validation of the Automated Imaging Differentiation in Parkinsonism (AID-P): A Multi-Site Machine Learning Study.

Derek B Archer, Ajay S. Kurani, Derek B. Archer, 2019, The Lancet. Digital health.

Wide Inference Network for Image Denoising pdf

Peng Liu, Ruogu Fang, Peng Liu, 2017, arXiv.org.

Anisotropic Tensor Total Variation Regularization For Low Dose Low CT Perfusion Deconvolution

Tsuhan Chen, P. Sanelli, R. Fang, 2014 .

Decoding Working Memory Load from High-Density EEG

D. Gilland, R. Fang, Chandni Rana, 2019 .

Identify diabetic retinopathy-related clinical concepts and their attributes using transformer-based natural language processing methods

Gianna L. Sweeting, Skylar E. Stolte, Xi Yang, 2022, BMC Medical Informatics and Decision Making.

DOMINO: Domain-Aware Model Calibration in Medical Image Segmentation

Skylar E. Stolte, A. Indahlastari, A. Woods, 2022, MICCAI.

Identify Cancer Patients at Risk for Heart Failure using Electronic Health Record and Genetic Data

Xi Yang, Y. Gong, R. Fang, 2022, 2022 IEEE 10th International Conference on Healthcare Informatics (ICHI).

Computational Health Informatics in the Big Data Age

Shu-Ching Chen, Yimin Yang, Samira Pouyanfar, 2016, ACM Comput. Surv..

Tree-metrics graph cuts for brain MRI segmentation with tree cutting

Tsuhan Chen, Ramin Zabih, Ruogu Fang, 2010, 2010 Western New York Image Processing Workshop.

Mining Big Neuron Morphological Data

Ruogu Fang, Maryamossadat Aghili, R. Fang, 2018, Comput. Intell. Neurosci..

REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs

Xiaoxiao Li, Joonho Lee, Peng Liu, 2019, Medical Image Anal..

Towards computational models of kinship verification

Tsuhan Chen, Noah Snavely, Ruogu Fang, 2010, 2010 IEEE International Conference on Image Processing.

Abdominal adipose tissues extraction using multi-scale deep neural network

Bin Sheng, Ruimin Shen, Fei Jiang, 2017, Neurocomputing.

Unraveling somatotopic organization in the human brain using machine learning and adaptive supervoxel-based parcellations

D. Vaillancourt, S. Coombes, R. Fang, 2021, NeuroImage.

Low-rise gable roof buildings pressure prediction using deep neural networks

Forrest J. Masters, Kurtis R. Gurley, Ruogu Fang, 2020 .

Retinal Microaneurysm Detection Using Clinical Report Guided Multi-sieving CNN

Qiang Wu, Bin Sheng, Ruogu Fang, 2017, MICCAI.

Identifying relations of medications with adverse drug events using recurrent convolutional neural networks and gradient boosting

Xi Yang, Yonghui Wu, Jiang Bian, 2019, J. Am. Medical Informatics Assoc..

Automatic Choroid Layer Segmentation from Optical Coherence Tomography Images Using Deep Learning

Qiang Wu, Ping Li, Bin Sheng, 2019, Scientific Reports.

Radiation dose reduction in computed tomography perfusion using spatial-temporal Bayesian methods

Tsuhan Chen, Ashish Raj, Pina C. Sanelli, 2012, Medical Imaging.

Domain-invariant interpretable fundus image quality assessment

Jing Qin, Bin Sheng, Dinggang Shen, 2020, Medical Image Anal..

CFEA: Collaborative Feature Ensembling Adaptation for Domain Adaptation in Unsupervised Optic Disc and Cup Segmentation pdf

Peng Liu, Shaoting Zhang, Ruogu Fang, 2019, MICCAI.

Kinship classification by modeling facial feature heredity

Tsuhan Chen, Alexander C. Loui, Andrew C. Gallagher, 2013, 2013 IEEE International Conference on Image Processing.

Baseline Neuroimaging Predicts Decline to Dementia From Amnestic Mild Cognitive Impairment

A. Woods, S. DeKosky, D. Loewenstein, 2021, Frontiers in Aging Neuroscience.

FedTiny: Pruned Federated Learning Towards Specialized Tiny Models

Xiaoyong Yuan, Lan Zhang, R. Fang, 2022, ArXiv.

A survey on medical image analysis in diabetic retinopathy

Skylar Stolte, Ruogu Fang, Skylar E. Stolte, 2020, Medical Image Anal..

Machine learning and individual variability in electric field characteristics predict tDCS treatment response

Skylar E. Stolte, A. Indahlastari, A. Woods, 2020, Brain Stimulation.

Sparsity-based deconvolution of low-dose brain perfusion CT in subarachnoid hemorrhage patients

Tsuhan Chen, Pina C. Sanelli, Ruogu Fang, 2012, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI).

Automatic Choroid Layer Segmentation from Optical Coherence Tomography Images Using Deep Learning

P. Li, J. Qin, W. Jia, 2019, Scientific Reports.

Automatic choroid layer segmentation using normalized graph cut

Qiang Wu, Bin Sheng, Ruimin Shen, 2018, IET Image Process..

Tissue-specific sparse deconvolution for brain CT perfusion

Junzhou Huang, Haodi Jiang, Ruogu Fang, 2015, Comput. Medical Imaging Graph..

Emergence of Emotion Selectivity in A Deep Neural Network Trained to Recognize Visual Objects

M. Ding, Peng Liu, R. Fang, 2023, bioRxiv.

STIR-Net: Deep Spatial-Temporal Image Restoration Net for Radiation Reduction in CT Perfusion

Yun Liang, Yao Xiao, Skylar Stolte, 2019, Front. Neurol..

Deep Spatial-Temporal Convolutional Neural Networks for Medical Image Restoration

Peng Liu, Ajay Gupta, Yao Xiao, 2019, Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics.

Big Data in Computational Health Informatics

S. Sitharama Iyengar, Yimin Yang, Samira Pouyanfar, 2019, Big Data in Multimodal Medical Imaging.

Robust Low-Dose CT Perfusion Deconvolution via Tensor Total-Variation Regularization

Tsuhan Chen, Shaoting Zhang, Pina C. Sanelli, 2015, IEEE Transactions on Medical Imaging.

Rotational and Reflectional Equivariant CNN for data-limited applications: Multiphase Flow demonstration

S. Balachandar, R. Fang, B. Siddani, 2021 .

A spatio-temporal low-rank total variation approach for denoising arterial spin labeling MRI data

Junzhou Huang, Wen-Ming Luh, Ruogu Fang, 2015, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).

Indexing and mining large-scale neuron databases using maximum inner product search

Fumin Shen, Shaoting Zhang, Zhongyu Li, 2017, Pattern Recognit..

Maximum inner product search for morphological retrieval of large-scale neuron data

Fumin Shen, Shaoting Zhang, Sailesh Conjeti, 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

CADA: Multi-scale Collaborative Adversarial Domain Adaptation for Unsupervised Optic Disc and Cup Segmentation pdf

Ruogu Fang, Bin Kong, Peng Liu, 2021, Neurocomputing.

Tensor Total-Variation Regularized Deconvolution for Efficient Low-Dose CT Perfusion

Tsuhan Chen, Shaoting Zhang, Pina C. Sanelli, 2014, MICCAI.

Towards robust deconvolution of low-dose perfusion CT: Sparse perfusion deconvolution using online dictionary learning

Tsuhan Chen, Pina C. Sanelli, Ruogu Fang, 2013, Medical Image Anal..

Development and validation of the automated imaging differentiation in parkinsonism (AID-P): a multicentre machine learning study.

Ajay S. Kurani, Derek B. Archer, Nikolaus R. McFarland, 2019, The Lancet. Digital health.

Wide Inference Network for Image Denoising

Ruogu Fang, Peng Liu, R. Fang, 2017, ArXiv.

Retinal Vessel Segmentation Using Minimum Spanning Superpixel Tree Detector

Qiang Wu, Ping Li, Bin Sheng, 2019, IEEE Transactions on Cybernetics.

Fast Preconditioning for Accelerated Multi-contrast MRI Reconstruction

Ruoyu Li, Junzhou Huang, Shaoting Zhang, 2015, MICCAI.

Learning Pixel-Distribution Prior with Wider Convolution for Image Denoising pdf

Peng Liu, Ruogu Fang, Peng Liu, 2017, ArXiv.

Identify Diabetic Retinopathy-related Clinical Concepts Using Transformer-based Natural Language Processing Methods

Ruogu Fang, Yinghan Ma, Xi Yang, 2021, 2021 IEEE 9th International Conference on Healthcare Informatics (ICHI).

Abdominal Adipose Tissue Segmentation in MRI with Double Loss Function Collaborative Learning

Ruogu Fang, Jing Qin, Siyuan Pan, 2019, MICCAI.

Rotational and reflectional equivariant convolutional neural network for data-limited applications: Multiphase flow demonstration

S. Balachandar, R. Fang, R. Fang, 2021, Physics of Fluids.

Towards Robust Deconvolution In Medical Imaging: Informatics, Diagnosis And Treatment

Ruogu Fang, R. Fang, 2014 .

Tissue-Specific Sparse Deconvolution for Low-Dose CT Perfusion

Tsuhan Chen, Pina C. Sanelli, Ruogu Fang, 2013, MICCAI.

Improving low-dose blood-brain barrier permeability quantification using sparse high-dose induced prior for Patlak model

Tsuhan Chen, Kolbeinn Karlsson, Pina C. Sanelli, 2014, Medical Image Anal..

Distributed Pruning Towards Tiny Neural Networks in Federated Learning

Dapeng Oliver Wu, Xiaoyong Yuan, Lan Zhang, 2022, 2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS).

Automatic choroid layer segmentation using normalized graph cut

R. Shen, Qiang Wu, Bin Sheng, 2018, IET Image Process..

Image Restoration Using Deep Regulated Convolutional Networks pdf

Peng Liu, Xiaoxiao Zhou, Ruogu Fang, 2019, ArXiv.

SDCNet: Smoothed dense-convolution network for restoring low-dose cerebral CT perfusion

Peng Liu, Ruogu Fang, Peng Liu, 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

Transfer-Gan: Multimodal Ct Image Super-Resolution Via Transfer Generative Adversarial Networks

Wesley E. Bolch, Ruogu Fang, Yao Xiao, 2020, 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).

Neural Network Evolution Using Expedited Genetic Algorithm for Medical Image Denoising

Peng Liu, Ruogu Fang, Mohammad D. El Basha, 2018, MICCAI.

Emergence of Emotion Selectivity in Deep Neural Networks Trained to Recognize Visual Objects

M. Ding, Peng Liu, R. Fang, 2024, PLoS Computational Biology.

LAVA: Granular Neuron-Level Explainable AI for Alzheimer's Disease Assessment from Fundus Images

M. Thai, Charlie Tran, A. Ramirez-Zamora, 2023, ArXiv.