Automatic Detection and Elimination of an Optic Disc for Improving Drusen Detection Accuracy

A. Prasath, M. Ramya
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引用次数: 6

Abstract

Precise localization of optic disc (OD) in color retinal images is an important sub-problem of automated retinal image analysis system. Drusen detection algorithms generally find lot of false positives at the OD region since the intensity of the drusen resembles with that of OD region. The exact identification an OD seems to be difficult as the disc boundaries are not clearly visible. Several parts of the disk is obscured by blood vessels. Further the size and position of the OD varies from one image to another. These factors make the OD detection a challenging task. In this paper we present a novel method to automatically detect the position of OD and eliminate it. The method starts with a color channel selection that provides a better contrast and reduces computational complexity. The contrast and the illumination of the image is normalized using adaptive histogram equalization (AHE) and homomorphic filtering respectively. The OD localization is then achieved by active contour segmentation using morphological operators. The algorithm is evaluated using 30 images. The proposed method was evaluated by comparing with conventional OD detection using a 2D circular Hough transform. The results prove an efficiency of the proposed method with an accuracy of 93%.
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视盘的自动检测与消除,提高Drusen检测精度
彩色视网膜图像视盘的精确定位是视网膜图像自动分析系统的一个重要子问题。由于Drusen的强度与OD区的强度相似,因此Drusen检测算法通常会在OD区发现大量的假阳性。确切的识别一个外径似乎是困难的,因为光盘边界不清楚可见。磁盘的几个部分被血管遮挡。此外,外径的大小和位置因图像而异。这些因素使得外径检测成为一项具有挑战性的任务。本文提出了一种自动检测外径位置并消除外径的新方法。该方法从颜色通道选择开始,以提供更好的对比度并降低计算复杂度。采用自适应直方图均衡化(AHE)和同态滤波分别对图像的对比度和照度进行归一化。然后利用形态学算子进行主动轮廓分割,实现OD定位。该算法使用30张图像进行评估。将该方法与传统的二维圆形霍夫变换外径检测方法进行了比较。结果证明了该方法的有效性,准确率达到93%。
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