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首页> 外文期刊>Biomedical signal processing and control >Blood vessel inpainting based technique for efficient localization and segmentation of optic disc in digital fundus images
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Blood vessel inpainting based technique for efficient localization and segmentation of optic disc in digital fundus images

机译：基于血管修复的数字眼底图像中视盘有效定位与分割技术

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The Optic disc (OD) nerve head region in general and OD center coordinates in particular form basis for study and analysis of various eye pathologies. The shape, contour and size of OD is vital in classification and grading of retinal diseases like glaucoma. There is a need to develop fast and efficient algorithms for large scale retinal disease screening. With this in mind, this paper present a novel framework for fast and fully automatic detection of OD and its accurate segmentation in digital fundus images. The methodology involves optic disc center localization followed by removal of vascular structure by accurate inpainting of blood vessels in the optic disc region. An adaptive threshold based Region Growing technique is then employed for reliable segmentation of fundus images. The proposed technique achieved significant results when tested on standard test databases like MESSIDOR and DRIVE with average overlapping ratio of 89% and 87%, respectively. Validation experiments were done on a labeled dataset containing healthy and pathological images obtained from a local eye hospital achieving an appreciable 91% average OD segmentation accuracy. (C) 2015 Elsevier Ltd. All rights reserved.
机译：视盘（OD）神经头区域通常与OD中心特别协调，形成了研究和分析各种眼部病理的基础。 OD的形状，轮廓和大小对于像青光眼这样的视网膜疾病的分类和分级至关重要。需要开发用于大规模视网膜疾病筛选的快速且有效的算法。考虑到这一点，本文提出了一种新颖的框架，可以快速，全自动地检测OD及其在数字眼底图像中的精确分割。该方法包括将视盘中心定位，然后通过在视盘区域中精确地修补血管来去除血管结构。然后采用基于自适应阈值的区域增长技术对眼底图像进行可靠的分割。当在标准测试数据库（例如MESSIDOR和DRIVE）上进行测试时，所提出的技术获得了显着的结果，平均重叠率分别为89％和87％。验证实验是在标记的数据集上进行的，该数据集包含从本地眼科医院获得的健康和病理图像，可实现91％的平均OD分割精度。 （C）2015 Elsevier Ltd.保留所有权利。

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