The Optimisation of Thresholding Techniques for the Identification of Choroidal Neovascular Membranes in Exudative Age-Related Macular Degeneration

E. Brankin, P. Mccullagh, N. Black, William Patton, A. Muldrew
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引用次数: 8

Abstract

The application of image processing to the investigation of age-related macular degeneration (AMD) has focused on detecting focal drusen deposits in retinal images. This research investigates algorithmic approaches in order to detect choroidal neovascularisation (CNV) from retinal fluorescein angiograms in exudative AMD, the most severe form of the disease. A combination of the 'Sobel' edge detection algorithm combined with thresholding produced the best qualitative segmentation, as verified by a trained ophthalmic grader. This study confirms that image processing can be used to identify certain types of CNV in retinal images particularly those that are hyper fluorescent. Further work is necessary to quantify the total lesion and characterise the clinically significant sub-components: classic or occult leakage, blood or exudate
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渗出性年龄相关性黄斑变性脉络膜新生血管膜阈值识别技术的优化
图像处理在年龄相关性黄斑变性(AMD)研究中的应用主要集中在检测视网膜图像中的局灶性黄斑沉积。本研究探讨了算法方法,以便从渗出性AMD(最严重的疾病形式)的视网膜荧光素血管造影中检测脉络膜新生血管(CNV)。“Sobel”边缘检测算法与阈值分割相结合,产生了最好的定性分割,经训练有素的眼科分级师验证。这项研究证实,图像处理可以用于识别视网膜图像中的某些类型的CNV,特别是那些超荧光的CNV。进一步的工作是必要的,以量化整个病变和表征临床重要的亚成分:典型或隐匿性渗漏,血液或渗出
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