Automatic Computerized Diagnostic Tool for Down Syndrome Detection in Fetus

M. D. Simon, A. Kavitha
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引用次数: 2

Abstract

Down syndrome is a genetic disorder and the chromosome abnormality observed in humans that can cause physical and mental abnormalities. It can never be cured or rectified. Instead it has to be identified in the fetus and prevented from being born. Many ultrasonographic markers like nuchal fold, nasal bone hypoplasia, femur length, and EIF are considered to be the symptoms of Down syndrome in the fetus. This chapter deals with the creation of automatic and computerized diagnostic tool for Down syndrome detection based on EIF. The proposed system consists of two phases: 1) training phase and 2) testing phase. In training phase, the fetal images with EIF and Down syndrome is analyzed and characteristics of EIF are collected. In testing phase, detection of Down syndrome is performed on the fetal image with EIF based on the knowledge cluster obtained using ESOM. The performance of the proposed system is analyzed in terms of sensitivity, accuracy, and specificity.
胎儿唐氏综合征检测的自动计算机诊断工具
唐氏综合症是一种遗传性疾病,在人类中观察到的染色体异常可导致身体和精神异常。它永远无法治愈或纠正。相反,它必须在胎儿中被识别出来,并在出生之前被阻止。许多超声标记如颈褶、鼻骨发育不全、股骨长度和EIF被认为是胎儿唐氏综合征的症状。本章讨论了基于EIF的唐氏综合征自动计算机诊断工具的创建。该系统包括两个阶段:1)训练阶段和2)测试阶段。在训练阶段,分析EIF和唐氏综合征的胎儿图像,收集EIF的特征。在检测阶段,基于ESOM获得的知识聚类,利用EIF对胎儿图像进行唐氏综合征检测。从灵敏度、准确性和特异性三个方面分析了该系统的性能。
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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