基于直方图特征的神经视网膜边缘区域分割用于视网膜眼底图像青光眼检测

A. Juliansyah, Gibran Satya Nugraha
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引用次数: 2

摘要

神经视网膜边缘是视盘和视杯之间的区域。神经视网膜边缘区由下、上、鼻、颞四部分组成。青光眼的诊断可以通过观察神经视网膜边缘的形状来完成。在正常的眼睛中,神经视网膜边缘的四个部分的大小遵循s规则,从最大到最小依次为:下、上、鼻和颞。本研究探讨了神经视网膜区域分割的自适应阈值。通过缩小视盘和视杯部分获得神经视网膜边缘区域。在此之前,通过分析均值和标准差值等直方图特征对视杯和视盘进行分割。正常图像的面积由大到小,符合眼瞳规则,但青光眼通常是先攻击下、上区域,使其出现缺口或变窄,违反眼瞳规则。该系统的准确率为91.25%,其中来自dristi - gs视网膜图像数据库的73幅图像成功诊断出有缺口的its区域,而8幅图像由于亮度较差仍未诊断出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Segmentation of Neuro Retinal Rim Area using Histogram Feature-based for Glaucoma Detection in Retinal Fundus Image
Neuro retinal rim is an area between optic disc and optic cup. Neuro retinal rim area consists of four parts, namely inferior, superior, nasal, and temporal (ISNT). The diagnosis of glaucoma can be done by observing the shape of the neuro retinal rim. In normal eyes, the size of the four parts in the neuro retinal rim follows the ISNT rule, from the largest to the smallest, as follows: inferior, superior, nasal, and temporal. This research was conducted to examine an adaptive threshold of neuro retinal area segmentation. The neuro retinal rim area was obtained by reducing the optic disc and the optic cup parts. Before that, optic cup and optic disc was segmented by analyzing histogram features likes mean and standard deviation values. Normal image has the area from the largest to the smallest according to the ISNT rules, however, in glaucoma, it is usually the inferior and superior areas attacked first, so that they experience notching or narrowing and violate the ISNT rules. The accuracy of the system was 91.25%, with 73 images from DRISTHI-GS retinal image database successfully diagnosed with the ISNT area that experienced notching, while the 8 images were still failed to diagnose due to a poor level of brightness.
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