Vessels Extraction from Retinal Images
Vessels Extraction from Retinal Images
复制标题
从视网膜图像中提取血管
DOI：
10.9790/2834-0637982
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Annapurna Singh
中科院分区：
文献类型：
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作者：
H. Bhadauria;S. S. Bisht;Annapurna Singh
糖尿病视网膜病变是人类眼病发病的主要原因。如果及早发现，眼病是可以预防的。在医学诊断和分析中，从视网膜图像中提取血管是一项重要而富有挑战性的任务。本文描述了利用Kirsch模板从视网膜图像中高效提取血管的方法。基尔希边缘算子使用罗盘旋转机制产生的八个滤波器来检测边缘。该方法用于自动检测眼底的标志性特征，如视盘、中央窝、血管等。视网膜血管的提取是诊断各种眼病的重要步骤。人眼视网膜图像对眼科医生的几种眼病的检测和诊断起着至关重要的作用（1-2）。彩色视网膜图像用于大规模筛查全身性疾病，如糖尿病视网膜病变（DR）。糖尿病视网膜病变的风险随着年龄的增长而增加，小血管受损。血管的长度、宽度、直径、分支模式等信息有助于疾病症状的诊断（3-4）。眼科医生可以检查视网膜图像，并通过搜索可能的异常，如糖尿病视网膜病变、青光眼和视网膜动脉闭塞等，给出诊断结果。在计算机辅助诊断（CAD）的帮助下，这些疾病的治疗成功率可能会显著提高。如果在早期（5-6）发现视网膜病变，可以预防糖尿病视网膜病变导致视力丧失的可能性。在（7-8）中描述了用于有效提取视网膜图像血管的基于滤波的方法。过去，人们使用各种技术从视网膜图像中提取血管。一种技术不仅可以找到起源于一组主要起始点的血管，还可以找到主要血管的所有分支。第二种方法采用匹配滤波（MF）提取血管。这种方法不仅会对血管做出响应，也会对非血管边缘做出响应(9)。第三种方法是一种新的混合自动提取视网膜图像血管的方法，该方法减少了弱边缘和噪声，最终实现了血管的提取。本文提出了一种利用Kirsch模板从视网膜图像中提取血管的方法。论文的其余部分分为5个部分。Kirsch边算子在第2节中描述。第3节解释了从视网膜图像中提取血管的方法。第4节给出了结果和讨论，最后在第5节给出了结论。
The main cause of eye diseases in the working human is Diabetic retinopathy. Eye disease can be prevented if detects early. The extraction of blood vessels from retinal images is an essential and challenging task in medical diagnosis and analysis. This paper describes the effective and efficient extraction of blood vessels from retinal image by using Kirsch's templates. The Kirsch's edge operators detect the edges using eight filters, generated by the compass rotation mechanism. The method is used to automatic detection of landmark features of the fundus, such as the optic disc, fovea and blood vessels. I. Introduction The extraction of Retinal blood vessel is an essential step for the diagnosis of various eye diseases. Retinal images of humans play a crucial role in the detection and diagnosis of several eye diseases for the oculists (1-2). Color retinal images are used in mass screen systemic diseases such as Diabetic Retinopathy (DR). The risk of the Diabetic Retinopa-thy increases with age and small eye blood vessels damaged the due to this disease. The information about blood vessels, such as length, width, diameter and branching pattern, can help to diagnose the symptom of diseases (3-4). The oculists may examine retinal images and give the diagnostic results by searching the possible anomalies like diabetic retinopathy, glaucoma and retinal artery occlusion. With the help of computer aided diagnosis (CAD), the success rate of the treatment of these diseases may increase significantly. If the retinopathy detects in early stage (5-6), the probability of visual loss resulting from diabetic retinopathy can be prevented. The filtering based method which is used for the effective extraction the blood vessels of retinal images are described in (7-8). In the past various techniques are used to extract the blood vessels from retinal images. One technique not only finds the blood vessels that originate from a set of primary starting point but also finds all branches off of the primary vessels. The second method use Matched Filter (MF) for the extraction of blood vessels. This method will respond not only to vessels but also to non-vessel edges (9). The third method is the novel hybrid automatic approach for the extraction of retinal image vessels which reduce the weak edges and noise, and finally results the blood vessels extraction. In this paper a method is proposed which uses the Kirsch's templates for the extraction of the blood vessels from retinal images. The rest of paper is organized into 5 Sections. The Kirsch's edge operators are described in Section 2. Section 3 explains proposed method for the extraction of blood vessels from retinal images. Section 4 shows the results and discussion and finally, the conclusion is given in Section 5.