...
首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Retinal vessels segmentation based on level set and region growing
【24h】

Retinal vessels segmentation based on level set and region growing

机译:基于水平集和区域增长的视网膜血管分割

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Retinal vessels play an important role in the diagnostic procedure of retinopathy. Accurate segmentation of retinal vessels is crucial for pathological analysis. In this paper, we propose a new retinal vessel segmentation method based on level set and region growing. Firstly, a retinal vessel image is preprocessed by the contrast-limited adaptive histogram equalization and a 2D Gabor wavelet to enhance the vessels. Then, an anisotropic diffusion filter is used to smooth the image and preserve vessel boundaries. Finally, the region growing method and a region-based active contour model with level set implementation are applied to extract retinal vessels, and their results are combined to achieve the final segmentation. Comparisons are conducted on the publicly available DRIVE and STARE databases using three different measurements. Experimental results show that the proposed method reaches an average accuracy of 94.77% on the DRIVE database and 95.09% on the STARE database.
机译:视网膜血管在视网膜病变的诊断过程中起着重要作用。视网膜血管的准确分割对于病理分析至关重要。在本文中,我们提出了一种新的基于水平集和区域增长的视网膜血管分割方法。首先,通过对比度受限的自适应直方图均衡和二维Gabor小波对视网膜血管图像进行预处理,以增强血管。然后,使用各向异性扩散滤镜来平滑图像并保留血管边界。最后,将区域生长方法和具有水平集实现的基于区域的主动轮廓模型应用于提取视网膜血管,并将其结果结合起来以实现最终分割。使用三种不同的度量对公开可用的DRIVE和STARE数据库进行比较。实验结果表明,该方法在DRIVE数据库中的平均准确率达到94.77%,在STARE数据库中的平均准确率达到95.09%。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号