Development of a detection system microaneurysms in color fundus images

M. M. A. Cervera, M. Paredes, R. Martinez, C. C. Ortiz, N. R. Hernandez
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引用次数: 6

Abstract

The detection of microaneurysms (MAs) in color fundus images remains an open issue in the medical image processing due to the low availability of reliable programs. In this paper, we present a system for automated detecting of MAs based with the techniques Hessian matrix and contrast limited adaptive histogram equalization (CLAHE). Thus, features extraction as optical disc, vascular tree and other pathologies for reducing false positives (FP). To evaluate the detection system MAs, we examined 81 color fundus images, classified by conditions and compared with fluorescence images, these are angiograms. The system provides a sensitivity of 15-24% in the phase of mild no proliferative diabetic retinopathy (DR) while in the phase of moderate no proliferative DR gave 10% sensitivity, in both phases the system detects more than 30 as candidates MAs. In healthy patients gives an average of 6 FP per image and patients with other diseases without DR less than 20 FP per image. Demonstrating that the system can work within different conditions, having a difference in results both in patients without DR as with DR, it which could be used in the early detection of disease.
眼底彩色图像微动脉瘤检测系统的研制
在彩色眼底图像中检测微动脉瘤(MAs)仍然是医学图像处理中的一个开放性问题,因为可靠的程序可用性低。本文提出了一种基于Hessian矩阵和对比度限制自适应直方图均衡化(CLAHE)技术的MAs自动检测系统。因此,特征提取作为光盘,血管树和其他病理减少假阳性(FP)。为了评价MAs检测系统,我们检查了81张彩色眼底图像,按条件分类,并与荧光图像进行比较,这些都是血管造影。该系统在轻度无增殖性糖尿病视网膜病变(DR)阶段的灵敏度为15-24%,而在中度无增殖性糖尿病视网膜病变(DR)阶段的灵敏度为10%,在这两个阶段,该系统都能检测到30多个候选MAs。在健康患者中,每张图像平均为6fp,而患有其他疾病而无DR的患者每张图像低于20fp。证明该系统可以在不同的条件下工作,在没有DR和DR的患者中都有不同的结果,这可以用于疾病的早期检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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