一种有效的视网膜图像血管检测算法分解.doc

AN EFFICIENT BLOOD VESSEL DETECTION ALGORITHM FOR RETINAL IMAGES 一种有效的视网膜图像血管检测算法 USING LOCAL ENTROPY THRESHOLDING 利用局部熵阈值 Thitiporn Chanwimaluang and Guoliang Fan School of Electrical and Computer Engineering 电气与计算机工程学院 Oklahoma State University, Stillwater, OK 74078 美国俄克拉荷马州立大学，静水，好74078 Email: {thitipo,glfan}@ 电子邮件：{ thitipo，glfan } @ ABSTRACT 摘要 This paper presents an efficient method for automatic detection and extraction of blood vessels in retinal images. Specifically, we also delineate vascular intersectionslcrossovers. The proposed al-gorithm is composed of four steps: matched filtering, local entropy thresholding, length filtering, and vascular intersection detection. The purpose of matched filtering is to enhance the blood vessels. Entropy-based thresholding can well keep the spatial structure of vascular tree segments. Length filtering is used to remove mis-classified pixels. The algorithm has been tested on twenty ocular fundus images, and experimental results are compared with those obtained from a state-of-the-art method and hand-labeled ground truth segmentations. 本文提出了一种有效的方法，用于自动检测和提取的血管在视网膜图像。具体来说，我们也划定血管intersectionslcrossovers。建议的铝去算法包括四个步骤：匹配滤波、局部熵的阈值，长度过滤，和血管的交叉点检测。匹配滤波的目的是增强血管。基于熵的阈值化能较好地保持血管树段的空间结构。长度滤波是用来删除错误分类的像素。二十眼基金的算法进行了测试我们的图像，实验结果与一个国家的最先进的方法和手工标记的地面真理分割得到的比较。 1. INTRODUCTION 1。简介 The automatic detection of blood vessels in the retinal images can 视网膜图像中血管的自动检测 help physicians for the purposes of diagnosing ocular diseases, pa-tient screening, and clinical study, etc. Information about blood 帮助医生诊断眼部疾病的目的，患者的筛查和临床研究，对血液等信息 vessels in retinal images can be used in grading disease sever-ity or as part of the process of automated diagnosis of diseases. Blood vessel appearance can provide information on pathological changes caused by some diseases including diabetes, hypertension, and arteriosclerosis. The most effective treatment for many eye-related diseases is the early detection through regular screenings. Furthermore, a segment