Retinal vessel segmentation of color fundus images using multiscale convolutional neural network with an improved cross-entropy loss function-Reference-Cited by-同舟云学术

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Retinal vessel segmentation of color fundus images using multiscale convolutional neural network with an improved cross-entropy loss function

Published:2018-10 Issue: Volume:309 Page:179-191
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Hu Kai,Zhang Zhenzhen,Niu Xiaorui,Zhang Yuan,Cao Chunhong,Xiao Fen,Gao Xieping

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference33 articles.

1. Hierarchical retinal blood vessel segmentation based on feature and ensemble learning;Wang;Neurocomputing,2015

2. Retinal vessel segmentation in colour fundus images using extreme learning machine;Zhu;Comput. Med. Imag. Graph.,2017

3. Retinal imaging and image analysis;Abrmoff;IEEE Rev. Biomed. Eng.,2010

4. Blood vessel segmentation methodologies in retinal images–a survey;Fraz;Comput. Methods Progr. Biomed.,2012

5. Segmentation of retinal blood vessels using a novel clustering algorithm (RACAL) with a partial supervision strategy;Salem;Med. Biol. Eng. Comput.,2007

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