眼底视网膜血管图像的自动分割方法研究

doi:10.11896/jsjkx.231000061

计算机科学 ›› 2024, Vol. 51 ›› Issue (11A): 231000061-7.doi: 10.11896/jsjkx.231000061

• 图像处理&多媒体技术 • 上一篇下一篇

眼底视网膜血管图像的自动分割方法研究

赵艳丽^1,2, 邢义通², 李小敏², 宋彩², 王培培²

1 东北大学计算机科学与工程学院沈阳 110819
2 宁夏理工学院电气信息工程学院宁夏石嘴山 753000

出版日期:2024-11-16 发布日期:2024-11-13
通讯作者: 邢义通(895628164@qq.com)
作者简介:(zhaoyanlimail@126.com)
基金资助:
宁夏自然科学基金(2023AAC03365)

Study on Automatic Segmentation Method of Retinal Blood Vessel Images

ZHAO Yanli^1,2, XING Yitong², LI Xiaomin², SONG Cai², WANG Peipei²

1 School of Computer Science and Engineering,Northeastern University,Shenyang 110819,China
2 School of Electrical Information Engineering,Ningxia Institute of Science and Technology,Shizuishan,Ningxia 753000,China

Online:2024-11-16 Published:2024-11-13
About author:ZHAO Yanli,born in 1986,doctoral candidate,lecturer.Her main research interests include computer vision and medical image-assisted diagnosis.
XING Yitong,born in 1989,doctoral candidate,lecturer.His main research interests include deep learning and fault diagnosis.
Supported by:
Natural Science Foundation of Ningxia Province(2023AAC03365).

摘要/Abstract

摘要： 随着计算机科学技术的快速发展,数字图像处理已被广泛用于医学辅助诊断中。鉴于人体健康状态与视网膜的血管管径、走向及分布紧密关联,视网膜图像评估已成为医生诊断的关键环节。然而,传统手工分割视网膜血管比较耗时且结果可复现性较差,已不适应当前需求。基于此,提出了一种基于图像处理的视网膜血管自动分割算法。该算法首先采用RGB彩色模型、直方图均衡化以及形态学方法对视网膜图像进行增强预处理,其次选用大津阈值法对图像的主干血管进行分割提取,之后通过高斯匹配滤波来动态调整阈值以实现小血管的分割,然后将分割后的主干及细小血管图像进行合并及优化,最后利用DRIVE图像库中的20张图像对该算法的性能进行了评估。结果表明,所提出的算法在准确度、灵敏度、特异度指标上分别达到了96.2%,77.3%,97.9%,从而验证了该算法的有效性和可靠性。

关键词: 视网膜图像, 血管分割, 图像预处理, 大津阈值, 高斯滤波器

Abstract: With the rapid advancement of computer science and technology,digital image processing is widely used in medical diagnostics.Due to the close correlation between human health and retinal vascular characteristics,evaluating retinal images has become crucial for medical diagnoses.Traditional manual retinal vessel segmentation is time-consuming and lacks reproducibility,no longer meeting current demands.Consequently,this paper introduces an automatic retinal vessel segmentation algorithm.Firstly,it uses RGB color model,histogram equalization and morphological methods to enhance the preprocessing of the retinal image.Secondly,the Otsu threshold method is used to segment and extract the main blood vessels of the image,and then the threshold is dynamically adjusted through Gaussian matching filtering to realize the segmentation of small blood vessels,and then merge and optimize the segmented main trunk and small blood vessel images.Finally,the performance of the proposed algorithm is assessed using 20 images from the DRIVE image database,demonstrating an average accuracy,sensitivity,and specificity of 96.2%,77.3%,and 97.9%,respectively,affirming its effectiveness and reliability.

Key words: Retinal images, Vascular segmentation, Image preprocessing, OTSU threshold, Gaussian filter

中图分类号:

TP391

赵艳丽, 邢义通, 李小敏, 宋彩, 王培培. 眼底视网膜血管图像的自动分割方法研究[J]. 计算机科学, 2024, 51(11A): 231000061-7. https://doi.org/10.11896/jsjkx.231000061

ZHAO Yanli, XING Yitong, LI Xiaomin, SONG Cai, WANG Peipei. Study on Automatic Segmentation Method of Retinal Blood Vessel Images[J]. Computer Science, 2024, 51(11A): 231000061-7. https://doi.org/10.11896/jsjkx.231000061

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眼底视网膜血管图像的自动分割方法研究

Study on Automatic Segmentation Method of Retinal Blood Vessel Images

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