Retinal vessel segmentation by improved matched filtering: evaluation on a new high‐resolution fundus image database 论文

2013IET Image Processing引用 468顶会
Retinal Imaging and AnalysisGlaucoma and retinal disordersDigital Imaging for Blood Diseases

详细信息

发表期刊/会议
IET Image Processing
发表日期
2013-06-01
发表年份
2013

关键词

Retinal Imaging and AnalysisGlaucoma and retinal disordersDigital Imaging for Blood Diseases

摘要

Automatic assessment of retinal vessels plays an important role in the diagnosis of various eye, as well as systemic diseases. A public screening is highly desirable for prompt and effective treatment, since such diseases need to be diagnosed at an early stage. Automated and accurate segmentation of the retinal blood vessel tree is one of the challenging tasks in the computer‐aided analysis of fundus images today. We improve the concept of matched filtering, and propose a novel and accurate method for segmenting retinal vessels. Our goal is to be able to segment blood vessels with varying vessel diameters in high‐resolution colour fundus images. All recent authors compare their vessel segmentation results to each other using only low‐resolution retinal image databases. Consequently, we provide a new publicly available high‐resolution fundus image database of healthy and pathological retinas. Our performance evaluation shows that the proposed blood vessel segmentation approach is at least comparable with recent state‐of‐the‐art methods. It outperforms most of them with an accuracy of 95% evaluated on the new database.

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