早产儿视网膜病变的随机鉴别方法

Srinivasan Prabakar, K. Porkumaran, R. Karthikeyan, Samson Isaac, R. Kannan, N. M. Nor, I. Elamvazuthi
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摘要

早产儿视网膜病变(ROP)是一种视网膜血管生长状况,通常影响出生体重在1500克以下、胎龄在32周或以下的早产儿。眼睛后部的视网膜捕捉光线并向大脑发送信号,形成眼睛的视觉。血管为视网膜提供氧气和营养,这些血管在怀孕后16-18周开始发育,并在正常分娩前完全成熟。早产会导致视网膜血管的发育,导致部分视网膜没有血管,从而导致儿童视力丧失。串行RetCam图像是从早产儿中获取的。采用绿色平面、直方图均衡化、对比度有限自适应直方图均衡化(CLAHE)三种预处理技术,可以得到视网膜血管与背景的最佳对比度。分割后进行分水岭变换,提取出6个统计特征。最后利用自适应神经模糊推理系统(ANFIS)分类器对图像进行正常和异常分类。
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Stochastic Approach for the Identification of Retinopathy of Prematurity
Retinopathy of Prematurity (ROP) is a retinal vessel growth condition that affects premature infants who usually are under a birth weight of 1,500 grams and have a gestational age of 32 weeks or less. The back portion of the eye, retina captures light and sends signals to the brain, creating the vision of eye. Blood vessels supply oxygen and nutrients to the retina and these blood vessels begin to develop at 16-18 weeks after conception, and complete with full maturity before the normal birth. Premature birth suffers the development of the retina vasculature and leaves some of the retina without blood vessels, which causes of visual loss in childhood. Serial RetCam images are acquired from premature infants. By applying three pre-processing techniques such as green colour plane, histogram equalization, Contrast Limited Adaptive Histogram Equalization (CLAHE), we can get the best contrast between the vessels and background of retina. After segmentation, watershed transform is applied, and then six statistical features are taken out from that image. Finally the images are categorized as normal or abnormal by using ANFIS (The Adaptive Neuro-Fuzzy Inference System) classifier.
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