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20172022
most citedCE-Net: Context Encoder Network for 2D Medical Image Segmentation

2.3k citations · 2.5k across the 11 of their papers we have counts for

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6 papers · 1 filter

cs.CV2021★ 4 cited

Adaptive Affinity Loss and Erroneous Pseudo-Label Refinement for Weakly Supervised Semantic Segmentation

Xiangrong Zhang, Zelin Peng, Peng Zhu +4

Semantic segmentation has been continuously investigated in the last ten years, and majority of the established technologies are based on supervised models. In recent years, image-…

cs.CV2021

Semantic Attention and Scale Complementary Network for Instance Segmentation in Remote Sensing Images

Tianyang Zhang, Xiangrong Zhang, Peng Zhu +4

In this paper, we focus on the challenging multicategory instance segmentation problem in remote sensing images (RSIs), which aims at predicting the categories of all instances and…

cs.CV2020★ 4 cited

A Two-Stream Meticulous Processing Network for Retinal Vessel Segmentation

Shaoming Zheng, Tianyang Zhang, Jiawei Zhuang +2

Vessel segmentation in fundus is a key diagnostic capability in ophthalmology, and there are various challenges remained in this essential task. Early approaches indicate that it i…

cs.CV2019★ 2 cited

Identify the cells' nuclei based on the deep learning neural network

Tianyang Zhang, Rui Ma

Identify the cells' nuclei is the important point for most medical analyses. To assist doctors finding the accurate cell' nuclei location automatically is highly demanded in the cl…

cs.CV2019★ 4 cited

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.CV2019★ 2.3k 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…