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Optic Disc Detection and Segmentation in Retinal Fundus Image

机译:视网膜眼底图像中的光盘检测和分割

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Segmentation of Optic Disc (OD) is one of the significant steps in automatic Diabetic Retinopathy (DR) detecting. Thus, DR detecting needs to eliminate the OD pixels. In this paper, a new technique is presented for OD segmentation that depends on the histogram template matching algorithm and OD size. The template matching algorithm is used for finding the center of the OD. In this step, the histogram of each RGB (Red, Green, and Blue) planes is found and then the cross-correlation is found between the template and the original image, OD location is the point with maximum cross-correlation between them. The OD size varies according to the camera field of sight and the resolution of the original image. The rectangle size of OD is not the same for various databases, the estimated size for the DRIVE, STARE, DIARTDB0, and DIARTDB1 are 80×80, 140×140, 190×190, and 190×190 respectively. After finding the OD center and rectangle size of OD, a binary mask is created with Region of Interest (ROI) for segmenting the OD. The DIARTDB0, DIARTDB1 and DRIVE are used to evaluate the proposed technique, the result was robust and vital with an accuracy of 96%, 98% and 98% respectively.
机译:光盘(OD)的分割是自动糖尿病视网膜病变(DR)检测中的重要步骤之一。因此,检测需要消除OD像素。在本文中,针对OD分段呈现了一种新技术,其取决于直方图模板匹配算法和OD大小。模板匹配算法用于查找OD的中心。在该步骤中,找到每个RGB(红色,绿色和蓝色)平面的直方图,然后在模板和原始图像之间发现互相关,OD位置是它们之间具有最大互相关的点。 OD大小根据相机视野和原始图像的分辨率而变化。各种数据库的OD的矩形大小不相同,驱动器的估计大小,凝视,DiarTDB0和DiarTDB1分别为80×80,140×140,190×190和190×190。在找到OD的OD中心和矩形大小后,使用兴趣区域(ROI)创建二进制掩码,用于分割OD。 DiaRTDB0,DiaRTDB1和驱动器用于评估所提出的技术,结果是鲁棒性和至关重要的,精度分别为96%,98%和98%。

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