早产儿视网膜病变自动筛查中附加疾病的诊断

R. Sivakumar, Manu Eldho, C. Jiji, A. Vinekar, R. John
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引用次数: 4

摘要

在印度等发展中国家,早产儿视网膜病变(ROP)的患病率在过去几十年中增加了许多倍。造成这一问题的主要原因是人们缺乏认识,诊断方法不当,筛查时专家之间的差异等。ROP是儿童失明的主要原因之一,根据Plus病的诊断,有必要对其进行治疗。血管扭曲与金标准图像的比较是其筛查的常用技术之一。该疾病的定量评估包括评估视网膜图像中的血管扭曲和血管扩张。我们提出了一种半自动化的基于计算机的方法来评估ROP中的Plus病。该方法首先对图像进行预处理,然后评估视网膜血管的弯曲度和宽度。在实现工作的基础上,EIARG2和KIDROP两个图像数据库定量分类为正、预正或正常情况,准确率较高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diagnosis of plus diseases for the automated screening of retinopathy of prematurity in preterm infants
The prevalence of Retinopathy of Prematurity (ROP) among preterm infants in the developing countries like India has increased many fold during the past decades. The main cause of this problem is lack of awareness among people, improper diagnostic methods, inter expert variability while screening etc. Treatment of ROP, one of the leading causes of childhood blindness is warranted based on the diagnosis of Plus disease. Comparison of tortuosity of blood vessels with a gold standard image was one of the common techniques used for its screening. Quantitative assessment of the disease includes evaluation of blood vessel tortuosity and vascular dilation in the retinal image. We present a semi-automated computer-based method for the assessment of Plus disease in ROP. This method involves initial preprocessing of the image followed by evaluation of tortuosity and width of retinal blood vessels. Based on the implemented work two image databases, EIARG2 and KIDROP were quantitatively classified as plus, pre-plus or normal case with high accuracy.
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