Retinal vessel segmentation based on task‐driven generative adversarial network-Reference-Cited by-同舟云学术

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Retinal vessel segmentation based on task‐driven generative adversarial network

Published:2020-12 Issue:17 Volume:14 Page:4599-4605
ISSN:1751-9659
Container-title:IET Image Processing
language:en
Short-container-title:IET image process

Author:

Chen Zhiyuan¹,Jin Wei¹,Zeng Xingbin²,Xu Liang¹

Affiliation:

1. Faculty of Electrical Engineering and Computer ScienceNingbo UniversityNingbo315211People's Republic of China

2. Intelligent Household Appliances Engineering CenterZhejiang Business Technology InstituteNingbo315012People's Republic of China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Natural Science Foundation of Ningbo

Ningbo University

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2020.1032

Reference29 articles.

1. A comprehensive texture segmentation framework for segmentation of capillary non‐perfusion regions in fundus fluorescein angiograms;Zheng Y.;Plos One,2014

2. Retinal arteriolar diameter and risk for hypertension;Wong T.Y.;Ann. Intern. Med.,2004

3. Retinal vessel segmentation in colour fundus images using extreme learning Machine;Zhu C.;Comput. Med. Imaging Graph., Off. J. Comput. Med. Imaging Soc.,2017

4. Retinal vessel segmentation by improved matched filtering: evaluation on a new high‐resolution fundus image database;Odstrcilik J.;IET Image Process.,2013

5. Segmentation of retinal blood vessels using normalized Gabor filters and automatic thresholding;Gwetu M.V.;S. Afr. Comput. J.,2014

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