.png){kind=icon}
返回
An adaptive threshold based image processing technique for improved glaucoma detection and classification
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cmpb.2015.08.002.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Glaucoma is an optic neuropathy which is one of the main causes of permanent blindness worldwide. This paper presents an automatic image processing based method for detection of glaucoma from the digital fundus images. In this proposed work, the discriminatory parameters of glaucoma infection, such as cup to disc ratio (CDR), neuro retinal rim (NRR) area and blood vessels in different regions of the optic disc has been used as features and fed as inputs to learning algorithms for glaucoma diagnosis. These features which have discriminatory changes with the occurrence of glaucoma are strategically used for training the classifiers to improve the accuracy of identification. The segmentation of optic disc and cup based on adaptive threshold of the pixel intensities lying in the optic nerve head region. Unlike existing methods the proposed algorithm is based on an adaptive threshold that uses local features from the fundus image for segmentation of optic cup and optic disc making it invariant to the quality of the image and noise content which may find wider acceptability. The experimental results indicate that such features are more significant in comparison to the statistical or textural features as considered in existing works. The proposed work achieves an accuracy of 94.11% with a sensitivity of 100%. A comparison of the proposed work with the existing methods indicates that the proposed approach has improved accuracy of classification glaucoma from a digital fundus which may be considered clinically significant. (C) 2015 Elsevier Ireland Ltd. All rights reserved.
Keyword:
Glaucoma
Optic disc
Optic cup
Cup to disc ratio
Adaptive threshold
Fundus image
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.8
论文数:
7.0K
被引数:
2.1W
机构
引用论文
Glaucoma risk index: Automated glaucoma detection from color fundus images.png)
MEDICAL IMAGE ANALYSIS
OAAI
MEDICAL IMAGE ANALYSISIF11.8
OAAI分享收藏分享收藏Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels使用血管的模糊收敛在视网膜图像中定位视神经
OAAI
OAAI分享收藏Automated detection of fovea in fundus images based on vessel-free zone and adaptive Gaussian template基于无血管区和自适应高斯模板的眼底图像中心凹自动检测
PREAI
分享收藏
查看更多内容