论文标题
比较视网膜脉管系统自动分割中不同的预处理方法
Comparing Different Preprocessing Methods in Automated Segmentation of Retinal Vasculature
论文作者
论文摘要
计算机方法和图像处理随时为医生提供帮助并减轻其工作量，尤其是在迭代过程中，例如识别感兴趣的对象，例如病变和图像中的解剖结构。在某些视网膜图像分析算法中，血管检测被认为是查找其他视网膜地标和病变及其相应直径的关键步骤，用于用于测量视网膜中对象的长度参考。这项研究的目的是比较两种预处理方法对视网膜边缘探测器的视网膜分割方法的影响（使用二阶空间差异），chary边缘检测器（估计梯度强度），以及在正常的金融书型透射率等视网膜图像中匹配的滤波器边缘探测器以及匹配的滤波器边缘检测器。从准确的角度来看，与眼科医生进行的手动分割相比，通过使用第一个预处理方法，照明均衡和对比度增强，chany，laplacian of-laplacian of-laplacian of-Gaussian和匹配过滤器容器裂片的精确度，对所有databases canse caster canse canse canse sect属于120张图像的视网膜图像。使用顶级预处理（第二种方法）进行分割方法的性能超过80％。最后，对于所有数据库的所有预处理步骤，使用匹配的过滤器对于血管分割具有最大精度。
Computer methods and image processing provide medical doctors assistance at any time and relieve their workload, especially for iterative processes like identifying objects of interest such as lesions and anatomical structures from the image. Vascular detection is considered to be a crucial step in some retinal image analysis algorithms to find other retinal landmarks and lesions, and their corresponding diameters, to use as a length reference to measure objects in the retina. The objective of this study is to compare the effect of two preprocessing methods on retinal vessel segmentation methods, Laplacian-of-Gaussian edge detector (using second-order spatial differentiation), Canny edge detector (estimating the gradient intensity), and Matched filter edge detector either in the normal fundus images or in the presence of retinal lesions like diabetic retinopathy. From the accuracy viewpoint, compared to manual segmentation performed by ophthalmologists for retinal images belonging to a test set of 120 images, by using first preprocessing method, Illumination equalization, and contrast enhancement, the accuracy of Canny, Laplacian-of-Gaussian, and Match filter vessel segmentation was more than 85% for all databases (MUMS-DB, DRIVE, MESSIDOR). The performance of the segmentation methods using top-hat preprocessing (the second method) was more than 80%. And lastly, using matched filter had maximum accuracy for the vessel segmentation for all preprocessing steps for all databases.
