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首页> 外文会议>Conference on image processing >Microaneurysms Detection with the Radon Cliff Operator in Retinal Fundus Images
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Microaneurysms Detection with the Radon Cliff Operator in Retinal Fundus Images

机译：用氡悬崖算子在视网膜眼底图像中进行微安瘤检测

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Diabetic Retinopathy (DR) is one of the leading causes of blindness in the industrialized world. Early detection is the key in providing effective treatment. However, the current number of trained eye care specialists is inadequate to screen the increasing number of diabetic patients. In recent years, automated and semi-automated systems to detect DR with color fundus images have been developed with encouraging, but not fully satisfactory results. In this study we present the initial results of a new technique for the detection and localization of microaneurysms, an early sign of DR. The algorithm is based on three steps: candidates selection, the actual microaneurysms detection and a final probability evaluation. We introduce the new Radon Cliff operator which is our main contribution to the field. Making use of the Radon transform, the operator is able to detect single noisy Gaussian-like circular structures regardless of their size or strength. The advantages over existing microaneurysms detectors are manifold: the size of the lesions can be unknown, it automatically distinguishes lesions from the vasculature and it provides a fair approach to microaneurysm localization even without post-processing the candidates with machine learning techniques, facilitating the training phase. The algorithm is evaluated on a publicly available dataset from the Retinopathy Online Challenge.
机译：糖尿病视网膜病变（DR）是工业化世界中失明的主要原因之一。早期检测是提供有效治疗的关键。然而，目前培训的眼科护理专家的数量不足以筛选患者患者越来越多的糖尿病患者。近年来，已经开发了自动化和半自动系统以令人鼓舞，但没有完全令人满意的结果，已经开发了用彩色眼底图像检测DR。在这项研究中，我们介绍了一种新技术的初始结果，用于微安瘤的检测和定位，博士的早期标志。该算法基于三个步骤：候选选择，实际的微安瘤检测和最终概率评估。我们介绍了新的氡悬崖操作员，这是我们对该领域的主要贡献。利用氡变换，操作员能够检测单个嘈杂的高斯圆形结构，无论其尺寸或强度如何。现有的微安瘤探测器的优点是歧管：病变的尺寸可能是未知的，它可以自动区分脉管系统的病变，即使在没有机器学习技术的候选人的情况下，也为微安患者定位提供了公平的方法，便于培训阶段。促进训练阶段。该算法在视网膜疗法在线挑战中对公共数据集进行评估。

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