RETINAL VESSELS EXTRACTION BASED ON IMPROVING LINE DETECTION

Hien Mong Nguyen
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Abstract

In the medical field, medical images have supported doctors in detecting some dangerous problems related to health. These problems are caused by abnormalities in retinal blood vessels. Therefore, analysis of retinal vascular features is a good way to detect these abnormalities that help doctors make suitable treatment plans in the early stage. One of the retinal analysis tasks is retinal blood vessel extraction which plays an important role because it needs to be done before any measurement can be created. This paper proposed an approach for retinal blood vessel extraction based on multi-scale line detection. In the proposed method, the input image is applied by a multi-scale line detection technique to detect retinal blood vessels. As a result, our method can work effectively to extract more vessels. The performance of the proposed method evaluates both quantitatively and qualitatively on publicly available DRIVE datasets with an accuracy average reaching 96%. The result of the proposed method is better than the other methods.
基于改进线检测的视网膜血管提取
在医疗领域,医学影像可以帮助医生发现一些与健康有关的危险问题。这些问题都是由视网膜血管异常引起的。因此,分析视网膜血管特征是检测这些异常的好方法,有助于医生在早期阶段制定合适的治疗方案。视网膜分析任务之一是视网膜血管提取,这项工作非常重要,因为在进行任何测量之前都需要提取血管。本文提出了一种基于多尺度线检测的视网膜血管提取方法。在所提出的方法中,输入图像通过多尺度线检测技术来检测视网膜血管。因此,我们的方法可以有效地提取更多的血管。在公开的 DRIVE 数据集上,对所提出方法的性能进行了定量和定性评估,平均准确率达到 96%。建议方法的结果优于其他方法。
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