activity
20192023
most citedREFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs

858 citations · 1.5k across the 26 of their papers we have counts for

collaborators
Showing 2020Show all

12 papers · 1 filter

cs.CV2020★ 11 cited

Attention-based Saliency Hashing for Ophthalmic Image Retrieval

Jiansheng Fang, Yanwu Xu, Xiaoqing Zhang +2

Deep hashing methods have been proved to be effective for the large-scale medical image search assisting reference-based diagnosis for clinicians. However, when the salient region…

cs.IR2020

Probabilistic Latent Factor Model for Collaborative Filtering with Bayesian Inference

Jiansheng Fang, Xiaoqing Zhang, Yan Hu +3

Latent Factor Model (LFM) is one of the most successful methods for Collaborative filtering (CF) in the recommendation system, in which both users and items are projected into a jo…

eess.IV2020★ 128 cited

Hierarchical Amortized Training for Memory-efficient High Resolution 3D GAN

Li Sun, Junxiang Chen, Yanwu Xu +3

Generative Adversarial Networks (GAN) have many potential medical imaging applications, including data augmentation, domain adaptation, and model explanation. Due to the limited me…

cs.CV2020★ 4 cited

Robust Collaborative Learning of Patch-level and Image-level Annotations for Diabetic Retinopathy Grading from Fundus Image

Yehui Yang, Fangxin Shang, Binghong Wu +5

Diabetic retinopathy (DR) grading from fundus images has attracted increasing interest in both academic and industrial communities. Most convolutional neural network (CNN) based al…

eess.IV2020

Residual-CycleGAN based Camera Adaptation for Robust Diabetic Retinopathy Screening

Dalu Yang, Yehui Yang, Tiantian Huang +3

There are extensive researches focusing on automated diabetic reti-nopathy (DR) detection from fundus images. However, the accuracy drop is ob-served when applying these models in…

eess.IV2020

Retinal Image Segmentation with a Structure-Texture Demixing Network

Shihao Zhang, Huazhu Fu, Yanwu Xu +2

Retinal image segmentation plays an important role in automatic disease diagnosis. This task is very challenging because the complex structure and texture information are mixed in…

eess.IV2020★ 25 cited

Robust Retinal Vessel Segmentation from a Data Augmentation Perspective

Xu Sun, Huihui Fang, Yehui Yang +4

Retinal vessel segmentation is a fundamental step in screening, diagnosis, and treatment of various cardiovascular and ophthalmic diseases. Robustness is one of the most critical r…

cs.CV2020★ 5 cited

Open-Narrow-Synechiae Anterior Chamber Angle Classification in AS-OCT Sequences

Huaying Hao, Huazhu Fu, Yanwu Xu +5

Anterior chamber angle (ACA) classification is a key step in the diagnosis of angle-closure glaucoma in Anterior Segment Optical Coherence Tomography (AS-OCT). Existing automated a…

eess.IV2020★ 1 cited

Reconstruction and Quantification of 3D Iris Surface for Angle-Closure Glaucoma Detection in Anterior Segment OCT

Jinkui Hao, Huazhu Fu, Yanwu Xu +5

Precise characterization and analysis of iris shape from Anterior Segment OCT (AS-OCT) are of great importance in facilitating diagnosis of angle-closure-related diseases. Existing…

cs.CV2020★ 9 cited

AGE Challenge: Angle Closure Glaucoma Evaluation in Anterior Segment Optical Coherence Tomography

Huazhu Fu, Fei Li, Xu Sun +22

Angle closure glaucoma (ACG) is a more aggressive disease than open-angle glaucoma, where the abnormal anatomical structures of the anterior chamber angle (ACA) may cause an elevat…

eess.IV2020★ 11 cited

A Thorough Comparison Study on Adversarial Attacks and Defenses for Common Thorax Disease Classification in Chest X-rays

Chendi Rao, Jiezhang Cao, Runhao Zeng +4

Recently, deep neural networks (DNNs) have made great progress on automated diagnosis with chest X-rays images. However, DNNs are vulnerable to adversarial examples, which may caus…

cs.CV2020★ 32 cited

Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution

Yong Guo, Jian Chen, Jingdong Wang +5

Deep neural networks have exhibited promising performance in image super-resolution (SR) by learning a nonlinear mapping function from low-resolution (LR) images to high-resolution…