Exudate segmentation on retinal atlas space

Sharib Ali, K. M. Adal, D. Sidibé, T. Karnowski, E. Chaum, F. Mériaudeau
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引用次数: 5

Abstract

Diabetic macular edema is characterized by hard exudates. Presence of such exudates cause vision loss in the affected areas. We present a novel approach of segmenting exudates for screening and follow-ups by building an ethnicity based statistical atlas. The chromatic distribution in such an atlas gives a good measure of probability of the pixels belonging to the healthy retinal pigments or to the abnormalities (like lesions, imaging artifacts etc.) in the retinal fundus image. Post-processing schemes are introduced in this paper for the enhancement of the edges of such exudates for final segmentation and to separate lesion from false positives. A sensitivity(recall) of 82.5 % at 35% of positive predictive value on FROC-curve is achieved. Results are obtained on a publicly available HEI-MED dataset and have been compared to two reference methods on the same dataset showing the competitiveness of the proposed algorithm.
视网膜图谱空间的渗出物分割
糖尿病性黄斑水肿以硬渗出物为特征。这种渗出物的存在会导致受影响区域的视力丧失。我们提出了一种通过建立基于种族的统计图谱来分割渗出物进行筛选和随访的新方法。这种图谱中的色度分布可以很好地衡量属于健康视网膜色素或视网膜眼底图像中异常(如病变、成像伪影等)的像素的概率。本文介绍了后处理方案,用于增强这些渗出物的边缘以进行最终分割,并将病变与假阳性区分开。在froc曲线阳性预测值的35%处,灵敏度(召回率)达到82.5%。结果是在一个公开的HEI-MED数据集上获得的,并与同一数据集上的两种参考方法进行了比较,显示了所提出算法的竞争力。
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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