Automatic localization of macular area based on structure label transfer

AIM: To explore feasibility and practicability of macula localization independent of macular morphological features. METHODS: A novel method was proposed to identify macula in fundus images by using structure label transfer. Its main idea was to match a processed image with the candidate images wit...

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Main Authors: Xiao-Xin Guo, Qun Li, Chao Sun, Yi-Nan Lu
Format: Article
Language:English
Published: Press of International Journal of Ophthalmology (IJO PRESS) 2018-03-01
Series:International Journal of Ophthalmology
Subjects:
428
Online Access:http://www.ijo.cn/en_publish/2018/3/20180312.pdf
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spelling doaj-40098a935f7b40ecb1a8bb27b6c8c99a2020-11-24T22:39:01ZengPress of International Journal of Ophthalmology (IJO PRESS)International Journal of Ophthalmology2222-39592227-48982018-03-0111342242810.18240/ijo.2018.03.12Automatic localization of macular area based on structure label transferXiao-Xin Guo0Qun Li1Chao Sun2Yi-Nan Lu3Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, Changchun130012, Jilin Province, China; College of Computer Science and Technology, Jilin University, Changchun 130012, Jilin Province, ChinaCollege of Computer Science and Technology, Jilin University, Changchun 130012, Jilin Province, ChinaCollege of Computer Science and Technology, Jilin University, Changchun 130012, Jilin Province, ChinaCollege of Computer Science and Technology, Jilin University, Changchun 130012, Jilin Province, ChinaAIM: To explore feasibility and practicability of macula localization independent of macular morphological features. METHODS: A novel method was proposed to identify macula in fundus images by using structure label transfer. Its main idea was to match a processed image with the candidate images with known structures, and then transfer the structure label representing the macular to the processed image as a result of macula localization. In this way, macula localization couldn’t be influenced by lesion or other interference any more. RESULTS: The average success rate in four datasets was 98.18%. For accuracy, the average error distance in four datasets was 0.151 optic disc diameter (ODD). Even for severe lesion images, the proposed method can still maintain high success rate and high accuracy, e.g., 95.65% and 0.124 ODD in the case of STARE dataset, respectively, which indicated that the proposed method was highly robust and stable in the complicated situations. CONCLUSION: The proposed method can avoid the interference of lesion to macular morphological features in macula localization, and can locate macula with high accuracy and robustness, verifying its feasibility.http://www.ijo.cn/en_publish/2018/3/20180312.pdf428fundus imageoptic discmaculastructure label transfer
collection DOAJ
language English
format Article
sources DOAJ
author Xiao-Xin Guo
Qun Li
Chao Sun
Yi-Nan Lu
spellingShingle Xiao-Xin Guo
Qun Li
Chao Sun
Yi-Nan Lu
Automatic localization of macular area based on structure label transfer
International Journal of Ophthalmology
428
fundus image
optic disc
macula
structure label transfer
author_facet Xiao-Xin Guo
Qun Li
Chao Sun
Yi-Nan Lu
author_sort Xiao-Xin Guo
title Automatic localization of macular area based on structure label transfer
title_short Automatic localization of macular area based on structure label transfer
title_full Automatic localization of macular area based on structure label transfer
title_fullStr Automatic localization of macular area based on structure label transfer
title_full_unstemmed Automatic localization of macular area based on structure label transfer
title_sort automatic localization of macular area based on structure label transfer
publisher Press of International Journal of Ophthalmology (IJO PRESS)
series International Journal of Ophthalmology
issn 2222-3959
2227-4898
publishDate 2018-03-01
description AIM: To explore feasibility and practicability of macula localization independent of macular morphological features. METHODS: A novel method was proposed to identify macula in fundus images by using structure label transfer. Its main idea was to match a processed image with the candidate images with known structures, and then transfer the structure label representing the macular to the processed image as a result of macula localization. In this way, macula localization couldn’t be influenced by lesion or other interference any more. RESULTS: The average success rate in four datasets was 98.18%. For accuracy, the average error distance in four datasets was 0.151 optic disc diameter (ODD). Even for severe lesion images, the proposed method can still maintain high success rate and high accuracy, e.g., 95.65% and 0.124 ODD in the case of STARE dataset, respectively, which indicated that the proposed method was highly robust and stable in the complicated situations. CONCLUSION: The proposed method can avoid the interference of lesion to macular morphological features in macula localization, and can locate macula with high accuracy and robustness, verifying its feasibility.
topic 428
fundus image
optic disc
macula
structure label transfer
url http://www.ijo.cn/en_publish/2018/3/20180312.pdf
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