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A stand-alone MATLAB application for the detection of Optic Disc and macula

机译:一个独立的MATLAB应用,用于检测光盘和斑块

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Glaucoma and Diabetic Retinopathy are the leading common cause of vision loss. Optic Disc and macula are the important landmark for the detection of these retinal pathology. Even though, the manual screening of Optic Disc and macula are available, they consume more time and have more human error. Therefore, there is a need of an automated application for the reliable and efficient localization of OD and macula. This paper presents a novel and fast stand-alone MATLAB application for the segmentation of these anatomical structures. This application uses colour K-means segmentation for locating macula and for detecting Optic Disc, bilateral filtering followed by Morphological operation is used. The application were evaluated on 135 glaucomatous images collected from local eye hospital and 200 diabetic retinopathy images from DIARETDB1 and DRIVE database. This stand-alone application consumes an average computation time of 13s for macula localization and 32s for OD segmentation with a success rate of 98%. Overall, the proposed application obtain an efficient result in the segmentation of both OD and macula, which in turn helps to detect glaucoma and Diabetic Retinopathy.
机译:青光眼和糖尿病视网膜病变是视力丧失的主要原因。光盘和黄斑是检测这些视网膜病理学的重要地标。即使,可以使用手动筛选光盘和黄斑,它们消耗更多的时间并具有更多的人为错误。因此,需要自动应用于OD和MACULA的可靠和有效的本地化。本文提出了一种新颖且快速独立的Matlab应用程序,用于分割这些解剖结构。本申请使用彩色k均值用于定位黄斑并用于检测光盘,使用双侧过滤,然后使用形态操作。在从尾乙酸和驱动数据库中从局部眼科医院和200糖尿病视网膜病图像收集的135个青光眼图像评估了申请。这种独立应用程序消耗PURUAL定位的平均计算时间为13秒,对于OD分割的32秒,成功率为98%。总的来说,所提出的应用获得了两种OD和黄斑的分割的有效结果,这反过来有助于检测青光眼和糖尿病视网膜病变。

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