眼底图像中黄斑检测的自动成像算法

Anushikha Singh, Namita Sengar, Ashish Issac, M. Dutta
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引用次数: 1

摘要

黄斑是人眼视网膜的重要组成部分,负责清晰的中心视觉。从眼底图像中准确、自动地检测黄斑是开发眼部病理自动筛查工具的必要步骤。提出了一种自动检测眼底图像中黄斑的成像方法。提出的方法包括一种基于窗口的策略方法,用于准确检测黄斑。该方法不是从眼底整幅图像中搜索黄斑,而是借助视盘考虑一个搜索区域,然后采用基于双窗口的方法在该搜索区域内检测黄斑。利用当地一家眼科医院的正常和受损眼底图像对所提出的方法进行了性能测试,取得了令人鼓舞的结果。提出的黄斑检测方法准确,计算成本低,因此可以帮助实时自动筛查各种眼病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An automated imaging algorithm for macula detection in fundus images
The Macula is an important part of the retina of human eye which is responsible for sharp central vision. Accurate and automatic detection of macula from fundus images is an essential step to develop automated screening tool for ocular pathologies. The proposed work presents an imaging method for detection of macula in fundus images automatically. The proposed method includes a strategic windowing based approach for accurate detection of macula. Instead of searching macula from whole fundus image, a search region is considered with the help of optic disc and then macula is detected from that search region using double windowing based method. Normal and affected fundus images from a local eye hospital were used to test the performance of proposed method and achieved encouraging results. The proposed method of macula detection is accurate, computationally cheap and hence can be helpful in real time automated screening of various eye diseases.
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