High‐quality retinal vessel segmentation using generative adversarial network with a large receptive field-Reference-Cited by-同舟云学术

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High‐quality retinal vessel segmentation using generative adversarial network with a large receptive field

Published:2020-04-09 Issue:3 Volume:30 Page:828-842
ISSN:0899-9457
Container-title:International Journal of Imaging Systems and Technology
language:en
Short-container-title:Int J Imaging Syst Technol

Author:

Zhao Hanli¹^ORCID,Qiu Xiaqing¹,Lu Wanglong¹,Huang Hui¹,Jin Xiaogang²

Affiliation:

1. College of Computer Science and Artificial IntelligenceWenzhou University Zhejiang China

2. State Key Lab of CAD&CGZhejiang University Zhejiang China

Funder

National Natural Science Foundation of China

Wenzhou Science and Technology Bureau

Zhejiang Provincial Natural Science Foundation

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Software,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ima.22428

Reference39 articles.

1. Trainable COSFIRE filters for vessel delineation with application to retinal images

2. Automated Vessel Segmentation Using Infinite Perimeter Active Contour Model with Hybrid Region Information with Application to Retinal Images

3. Robust Retinal Vessel Segmentation via Locally Adaptive Derivative Frames in Orientation Scores

4. Blood vessel segmentation of fundus images by major vessel extraction and subimage classification;Roychowdhury S;IEEE J Biomed Health Inform,2015

5. Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification

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