most citedCE-Net: Context Encoder Network for 2D Medical Image Segmentation

2.3k citations · 2.3k across the 4 of their papers we have counts for

collaborators

6 papers

eess.IV202021 cited

Encoding Structure-Texture Relation with P-Net for Anomaly Detection in Retinal Images

Kang Zhou, Yuting Xiao, Jianlong Yang +6

Anomaly detection in retinal image refers to the identification of abnormality caused by various retinal diseases/lesions, by only leveraging normal images in training phase. Norma…

cs.CV20196 cited

Sparse-GAN: Sparsity-constrained Generative Adversarial Network for Anomaly Detection in Retinal OCT Image

Kang Zhou, Shenghua Gao, Jun Cheng +6

With the development of convolutional neural network, deep learning has shown its success for retinal disease detection from optical coherence tomography (OCT) images. However, dee…

eess.IV20193 cited

Dense Dilated Network with Probability Regularized Walk for Vessel Detection

Lei Mou, Li Chen, Jun Cheng +3

The detection of retinal vessel is of great importance in the diagnosis and treatment of many ocular diseases. Many methods have been proposed for vessel detection. However, most o…

eess.IV2019

The Channel Attention based Context Encoder Network for Inner Limiting Membrane Detection

Hao Qiu, Zaiwang Gu, Lei Mou +5

The optic disc segmentation is an important step for retinal image-based disease diagnosis such as glaucoma. The inner limiting membrane (ILM) is the first boundary in the OCT, whi…

cs.CV2019

SkrGAN: Sketching-rendering Unconditional Generative Adversarial Networks for Medical Image Synthesis

Tianyang Zhang, Huazhu Fu, Yitian Zhao +7

Generative Adversarial Networks (GANs) have the capability of synthesizing images, which have been successfully applied to medical image synthesis tasks. However, most of existing…

cs.CV20192.3k cited

CE-Net: Context Encoder Network for 2D Medical Image Segmentation

Zaiwang Gu, Jun Cheng, Huazhu Fu +6

Medical image segmentation is an important step in medical image analysis. With the rapid development of convolutional neural network in image processing, deep learning has been us…