A Morphological Hessian Based Approach for Retinal Blood Vessels Segmentation and Denoising Using Region Based Otsu Thresholding.
A Morphological Hessian Based Approach for Retinal Blood Vessels Segmentation and Denoising Using Region Based Otsu Thresholding.
复制标题
DOI：
10.1371/journal.pone.0158996
复制
发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Shahid M
中科院分区：
文献类型：
--
作者：
BahadarKhan K;A Khaliq A;Shahid M
糖尿病视网膜病变（DR）损害眼睛中的视网膜血管，导致视力缺陷。视网膜图像中血管的形态和结构在眼科疾病的诊断中起着重要的作用。我们提出了一种计算量较小的无监督自动化技术，通过使用基于形态学海森的方法和基于区域的大津阈值检测视网膜血管有希望的结果。对比度受限自适应直方图均衡（CLAHE）和形态滤波器已分别用于增强和去除低频噪声或几何对象。所使用的海森矩阵和特征值方法已经在两个不同尺度上以修改的形式分别提取宽血管和薄血管增强图像。大津阈值已被进一步应用在一种新的方式来分类血管和非血管像素从两个增强的图像。最后，使用后处理步骤来消除不需要的区域/段、非血管像素、疾病异常和噪声，以获得最终的分割图像。所提出的技术已经分析了开放访问的DRIVE（数字视网膜图像血管提取）和STARE（结构化分析的视网膜）数据库沿着的地面实况数据，已被专家精确标记。
Diabetic Retinopathy (DR) harm retinal blood vessels in the eye causing visual deficiency. The appearance and structure of blood vessels in retinal images play an essential part in the diagnoses of an eye sicknesses. We proposed a less computational unsupervised automated technique with promising results for detection of retinal vasculature by using morphological hessian based approach and region based Otsu thresholding. Contrast Limited Adaptive Histogram Equalization (CLAHE) and morphological filters have been used for enhancement and to remove low frequency noise or geometrical objects, respectively. The hessian matrix and eigenvalues approach used has been in a modified form at two different scales to extract wide and thin vessel enhanced images separately. Otsu thresholding has been further applied in a novel way to classify vessel and non-vessel pixels from both enhanced images. Finally, postprocessing steps has been used to eliminate the unwanted region/segment, non-vessel pixels, disease abnormalities and noise, to obtain a final segmented image. The proposed technique has been analyzed on the openly accessible DRIVE (Digital Retinal Images for Vessel Extraction) and STARE (STructured Analysis of the REtina) databases along with the ground truth data that has been precisely marked by the experts.