Retinal blood vessel segmentation based on fractal dimension in spatial-frequency domain
Retinal blood vessel segmentation based on fractal dimension in spatial-frequency domain
复制标题
基于空间频域分形维数的视网膜血管分割
DOI：
10.1109/iscit.2010.5665170
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
K. Higuchi
中科院分区：
文献类型：
--
作者：
Sukritta Paripurana;W. Chiracharit;K. Chamnongthai;K. Higuchi
在眼底图像自动筛选系统中，血管分割是非常重要的。在检测到其他残留病变之前，血管通常被分割并从视网膜图像中移除。血管切除不彻底往往会导致病变检测的假阳性，特别是对微动脉瘤的检测。由于视网膜图像中的无光照和噪声，在空间图像域分割血管会造成漏检。通过在空间-频域分割血管可以忽略无光照问题，可以忽略哪些不变子带可以忽略。提出了一种新的基于分维的视网膜图像空频域视网膜血管分割方法。为了从视网膜背景中提取血管，计算每个像素的分维值。对该方法的性能进行了评估，并与STARE数据库中的专家诊断结果进行了比较。
Vessel segmentation is very important in an automatic screening system for fundus images. Vessels are often segmented and removed from retinal images before the other residual lesions are detected. Incomplete vessel removal usually causes a false positive in lesion detection, especially for Microaneurysms detection. Segmenting vessels in spatial image domain makes miss detection due to non illumination and noises in retinal images. Non-illumination problem can be disregarded by segmenting the vessels in spatial-frequency domain, which invariant subbands can be ignored. This paper presents a new retinal blood vessel segmentation method based on fractal dimension in spatial-frequency domain of retinal images. The fractal dimension value of each pixel is computed in order to extract the vessels from their retinal background. The performance of the proposed method is evaluated and compared with the experts' diagnosis in the STARE database.